US20160378747A1 - Virtual assistant for media playback - Google Patents
Virtual assistant for media playback Download PDFInfo
- Publication number
- US20160378747A1 US20160378747A1 US14/819,343 US201514819343A US2016378747A1 US 20160378747 A1 US20160378747 A1 US 20160378747A1 US 201514819343 A US201514819343 A US 201514819343A US 2016378747 A1 US2016378747 A1 US 2016378747A1
- Authority
- US
- United States
- Prior art keywords
- user
- media
- user input
- context
- media item
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
Images
Classifications
-
- G06F17/28—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/16—Sound input; Sound output
- G06F3/167—Audio in a user interface, e.g. using voice commands for navigating, audio feedback
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
- G06F16/48—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
-
- G06F17/30684—
-
- G06F17/30864—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/169—Annotation, e.g. comment data or footnotes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/26—Speech to text systems
Definitions
- the present disclosure relates generally to media playback, and more specifically to a virtual assistant used to facilitate media playback.
- Intelligent automated assistants provide a beneficial interface between human users and electronic devices.
- Such assistants allow users to interact with devices or systems using natural language in spoken and/or text forms.
- a user can access the services of an electronic device by providing a spoken user request to a digital assistant associated with the electronic device.
- the digital assistant can interpret the user's intent from the spoken user request and operationalize the user's intent into tasks. The tasks can then be performed by executing one or more services of the electronic device and a relevant output can be returned to the user in natural language form.
- a digital assistant When managing music or other media, a digital assistant can be helpful in playing back specific media, particularly in a hands-free environment.
- a digital assistant can respond effectively to a request to play a specific media item, such as an album or a song identified specifically by title or by artist.
- digital assistants have not been useful in discovering media based on nonspecific, unstructured natural language requests—for example, a request for a song from a popular movie.
- Some techniques for discovering media based on a nonspecific, unstructured natural language request are generally cumbersome and inefficient.
- existing techniques use a complex and time-consuming user interface, which may include multiple key presses or keystrokes. The user must perform his or her own research to determine which specific media he or she is seeking, then attempt to obtain that media. Both of those steps may be impractical or impossible in certain circumstances, such as when the user is operating a motor vehicle or has his or her hands full.
- Existing techniques require more time than necessary, wasting user time and device energy. This latter consideration is particularly important in battery-operated devices.
- a method for identifying media includes: at a device with one or more processors, memory, and a microphone: receiving user input associated with a request for media, the user input including unstructured natural language speech including one or more words; identifying at least one context associated with the user input; causing a search for the media based on the at least one context and the user input; determining, based on the at least one context and the user input, at least one media item that satisfies the request; and, in accordance with a determination that the at least one media item satisfies the request, obtaining the at least one media item.
- an electronic device includes: a display; a memory; a microphone; a processor coupled to the display, the memory, and the microphone; the processor configured to: receive user input associated with a request for media, the user input including unstructured natural language speech including one or more words; identify at least one context associated with the user input; cause a search for the media based on the at least one context and the user input; determine, based on the at least one context and the user input, at least one media item that satisfies the request; and, in accordance with a determination that the at least one media item satisfies the request, obtain the at least one media item.
- a non-transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to: receive user input associated with a request for media, the user input including unstructured natural language speech including one or more words; identify at least one context associated with the user input; cause a search for the media based on the at least one context and the user input; determine, based on the at least one context and the user input, at least one media item that satisfies the request; and in accordance with a determination that the at least one media item satisfies the request, obtain the at least one media item.
- a transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to: receive user input associated with a request for media, the user input including unstructured natural language speech including one or more words; identify at least one context associated with the user input; cause a search for the media based on the at least one context and the user input; determine, based on the at least one context and the user input, at least one media item that satisfies the request; and, in accordance with a determination that the at least one media item satisfies the request, obtain the at least one media item.
- a system utilizes an electronic device with a display, where the system includes: means for receiving user input associated with a request for media, the user input including unstructured natural language speech including one or more words; means for identifying at least one context associated with the user input; means for causing a search for the media based on the at least one context and the user input; means for determining, based on the at least one context and the user input, at least one media item that satisfies the request; and, in accordance with a determination that the at least one media item satisfies the request, means for obtaining the at least one media item.
- an electronic device includes: a processing unit that includes a receiving unit, an identifying unit, a causing unit, a determining unit, and an obtaining unit, the processing unit configured to: receive, using the receiving unit, user input associated with a request for media, the user input including unstructured natural language speech including one or more words; identify, using the identifying unit, at least one context associated with the user input; cause, using the causing unit, a search for the media based on the at least one context and the user input; determine, using the determining unit, based on the at least one context and the user input, at least one media item that satisfies the request; and, in accordance with a determination that the at least one media item satisfies the request, obtain, using the obtaining unit, the at least one media item.
- Executable instructions for performing these functions are, optionally, included in a non-transitory computer-readable storage medium or other computer program product configured for execution by one or more processors. Executable instructions for performing these functions are, optionally, included in a transitory computer-readable storage medium or other computer program product configured for execution by one or more processors.
- devices are provided with faster, more efficient methods and interfaces for discovering media based on a nonspecific, unstructured natural language request, thereby increasing the effectiveness, efficiency, and user satisfaction with such devices.
- Such methods and interfaces may complement or replace other methods for discovering media based on a nonspecific, unstructured natural language request.
- FIG. 1 is a block diagram illustrating a system and environment for implementing a digital assistant according to various examples.
- FIG. 2A is a block diagram illustrating a portable multifunction device implementing the client-side portion of a digital assistant according to various examples.
- FIG. 2B is a block diagram illustrating exemplary components for event handling according to various examples.
- FIG. 3 illustrates a portable multifunction device implementing the client-side portion of a digital assistant according to various examples.
- FIG. 4 is a block diagram of an exemplary multifunction device with a display and a touch-sensitive surface according to various examples.
- FIG. 5A illustrates an exemplary user interface for a menu of applications on a portable multifunction device according to various examples.
- FIG. 5B illustrates an exemplary user interface for a multifunction device with a touch-sensitive surface that is separate from the display according to various examples.
- FIG. 6A illustrates a personal electronic device according to various examples.
- FIG. 6B is a block diagram illustrating a personal electronic device according to various examples.
- FIG. 7A is a block diagram illustrating a digital assistant system or a server portion thereof according to various examples.
- FIG. 7B illustrates the functions of the digital assistant shown in FIG. 7A according to various examples.
- FIG. 7C illustrates a portion of an ontology according to various examples.
- FIGS. 8A-8Q illustrate exemplary user interfaces for a personal electronic device in accordance with some embodiments.
- FIG. 8I is intentionally omitted to avoid any confusion between the capital letter I and the numeral 1 (one), and
- FIG. 8O is intentionally omitted to avoid any confusion between the capital letter O and the numeral 0 (zero).
- FIGS. 9A-9C illustrate a process for operating a digital assistant for media playback, according to various examples.
- FIG. 10 illustrates a functional block diagram of an electronic device according to various examples.
- a digital assistant can reduce the cognitive burden on a user who discovers media based on a nonspecific, unstructured natural language request, thereby enhancing productivity. Further, such techniques can reduce processor and battery power otherwise wasted on redundant user inputs.
- FIGS. 1, 2A-2B, 3, 4, 5A-5B and 6A-6B provide a description of exemplary devices for performing the techniques for discovering media based on a nonspecific, unstructured natural language request.
- FIG. 6A-6B illustrate exemplary user interfaces for discovering media based on a nonspecific, unstructured natural language request.
- FIGS. 7A-7C are block diagrams illustrating a digital assistant system or a server portion thereof, and a portion of an ontology associated with the digital assistant system.
- FIGS. 8A-8B are flow diagrams illustrating methods of discovering media based on a nonspecific, unstructured natural language request in accordance with some embodiments.
- first could be termed a second touch
- first touch could be termed a first touch
- second touch could be termed a first touch
- the first touch and the second touch are both touches, but they are not the same touch.
- if may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context.
- phrase “if it is determined” or “if [a stated condition or event] is detected” may be construed to mean “upon determining” or “in response to determining” or “upon detecting [the stated condition or event]” or “in response to detecting [the stated condition or event],” depending on the context.
- the device is a portable communications device, such as a mobile telephone, that also contains other functions, such as PDA and/or music player functions.
- portable multifunction devices include, without limitation, the iPhone®, iPod Touch®, and iPad® devices from Apple Inc. of Cupertino, Calif.
- Other portable electronic devices such as laptops or tablet computers with touch-sensitive surfaces (e.g., touch screen displays and/or touchpads), are, optionally, used.
- the device is not a portable communications device, but is a desktop computer with a touch-sensitive surface (e.g., a touch screen display and/or a touchpad).
- an electronic device that includes a display and a touch-sensitive surface is described. It should be understood, however, that the electronic device optionally includes one or more other physical user-interface devices, such as a physical keyboard, a mouse, and/or a joystick.
- the device may support a variety of applications, such as one or more of the following: a drawing application, a presentation application, a word processing application, a website creation application, a disk authoring application, a spreadsheet application, a gaming application, a telephone application, a video conferencing application, an e-mail application, an instant messaging application, a workout support application, a photo management application, a digital camera application, a digital video camera application, a web browsing application, a digital music player application, and/or a digital video player application.
- applications such as one or more of the following: a drawing application, a presentation application, a word processing application, a website creation application, a disk authoring application, a spreadsheet application, a gaming application, a telephone application, a video conferencing application, an e-mail application, an instant messaging application, a workout support application, a photo management application, a digital camera application, a digital video camera application, a web browsing application, a digital music player application, and/or a digital video player application.
- the various applications that are executed on the device optionally use at least one common physical user-interface device, such as the touch-sensitive surface.
- One or more functions of the touch-sensitive surface as well as corresponding information displayed on the device are, optionally, adjusted and/or varied from one application to the next and/or within a respective application.
- a common physical architecture (such as the touch-sensitive surface) of the device optionally supports the variety of applications with user interfaces that are intuitive and transparent to the user.
- FIG. 1 illustrates a block diagram of system 100 according to various examples.
- system 100 can implement a digital assistant.
- digital assistant can refer to any information processing system that interprets natural language input in spoken and/or textual form to infer user intent, and performs actions based on the inferred user intent.
- the system can perform one or more of the following: identifying a task flow with steps and parameters designed to accomplish the inferred user intent, inputting specific requirements from the inferred user intent into the task flow; executing the task flow by invoking programs, methods, services, APIs, or the like; and generating output responses to the user in an audible (e.g., speech) and/or visual form.
- identifying a task flow with steps and parameters designed to accomplish the inferred user intent inputting specific requirements from the inferred user intent into the task flow
- executing the task flow by invoking programs, methods, services, APIs, or the like
- output responses to the user in an audible (e.g., speech) and/or visual form.
- audible e.g., speech
- a digital assistant can be capable of accepting a user request at least partially in the form of a natural language command, request, statement, narrative, and/or inquiry.
- the user request can seek either an informational answer or performance of a task by the digital assistant.
- a satisfactory response to the user request can be a provision of the requested informational answer, a performance of the requested task, or a combination of the two.
- a user can ask the digital assistant a question, such as “Where am I right now?” Based on the user's current location, the digital assistant can answer, “You are in Central Park near the west gate.” The user can also request the performance of a task, for example, “Please invite my friends to my girlfriend's birthday party next week.” In response, the digital assistant can acknowledge the request by saying “Yes, right away,” and then send a suitable calendar invite on behalf of the user to each of the user's friends listed in the user's electronic address book.
- the digital assistant can sometimes interact with the user in a continuous dialogue involving multiple exchanges of information over an extended period of time.
- the digital assistant can also provide responses in other visual or audio forms, e.g., as text, alerts, music, videos, animations, etc.
- a digital assistant can be implemented according to a client-server model.
- the digital assistant can include client-side portion 102 (hereafter “DA client 102 ”) executed on user device 104 and server-side portion 106 (hereafter “DA server 106 ”) executed on server system 108 .
- DA client 102 can communicate with DA server 106 through one or more networks 110 .
- DA client 102 can provide client-side functionalities such as user-facing input and output processing and communication with DA server 106 .
- DA server 106 can provide server-side functionalities for any number of DA clients 102 each residing on a respective user device 104 .
- DA server 106 can include client-facing I/O interface 112 , one or more processing modules 114 , data and models 116 , and I/O interface to external services 118 .
- the client-facing I/O interface 112 can facilitate the client-facing input and output processing for DA server 106 .
- One or more processing modules 114 can utilize data and models 116 to process speech input and determine the user's intent based on natural language input. Further, one or more processing modules 114 perform task execution based on inferred user intent.
- DA server 106 can communicate with external services 120 through network(s) 110 for task completion or information acquisition. I/O interface to external services 118 can facilitate such communications.
- User device 104 can be any suitable electronic device.
- user devices can be a portable multifunctional device (e.g., device 200 , described below with reference to FIG. 2A ), a multifunctional device (e.g., device 400 , described below with reference to FIG. 4 ), or a personal electronic device (e.g., device 600 , described below with reference to FIG. 6A-B .)
- a portable multifunctional device can be, for example, a mobile telephone that also contains other functions, such as PDA and/or music player functions.
- Specific examples of portable multifunction devices can include the iPhone®, iPod Touch®, and iPad® devices from Apple Inc. of Cupertino, Calif.
- Other examples of portable multifunction devices can include, without limitation, laptop or tablet computers.
- user device 104 can be a non-portable multifunctional device.
- user device 104 can be a desktop computer, a game console, a television, or a television set-top box.
- user device 104 can include a touch-sensitive surface (e.g., touch screen displays and/or touchpads).
- user device 104 can optionally include one or more other physical user-interface devices, such as a physical keyboard, a mouse, and/or a joystick.
- electronic devices such as multifunctional devices, are described below in greater detail.
- Examples of communication network(s) 110 can include local area networks (LAN) and wide area networks (WAN), e.g., the Internet.
- Communication network(s) 110 can be implemented using any known network protocol, including various wired or wireless protocols, such as, for example, Ethernet, Universal Serial Bus (USB), FIREWIRE, Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Wi-Fi, voice over Internet Protocol (VoIP), Wi-MAX, or any other suitable communication protocol.
- Server system 108 can be implemented on one or more standalone data processing apparatus or a distributed network of computers.
- server system 108 can also employ various virtual devices and/or services of third-party service providers (e.g., third-party cloud service providers) to provide the underlying computing resources and/or infrastructure resources of server system 108 .
- third-party service providers e.g., third-party cloud service providers
- user device 104 can communicate with DA server 106 via second user device 122 .
- Second user device 122 can be similar or identical to user device 104 .
- second user device 122 can be similar to devices 200 , 400 , or 600 described below with reference to FIGS. 2A, 4, and 6A -B.
- User device 104 can be configured to communicatively couple to second user device 122 via a direct communication connection, such as Bluetooth, NFC, BTLE, or the like, or via a wired or wireless network, such as a local Wi-Fi network.
- second user device 122 can be configured to act as a proxy between user device 104 and DA server 106 .
- DA client 102 of user device 104 can be configured to transmit information (e.g., a user request received at user device 104 ) to DA server 106 via second user device 122 .
- DA server 106 can process the information and return relevant data (e.g., data content responsive to the user request) to user device 104 via second user device 122 .
- user device 104 can be configured to communicate abbreviated requests for data to second user device 122 to reduce the amount of information transmitted from user device 104 .
- Second user device 122 can be configured to determine supplemental information to add to the abbreviated request to generate a complete request to transmit to DA server 106 .
- This system architecture can advantageously allow user device 104 having limited communication capabilities and/or limited battery power (e.g., a watch or a similar compact electronic device) to access services provided by DA server 106 by using second user device 122 , having greater communication capabilities and/or battery power (e.g., a mobile phone, laptop computer, tablet computer, or the like), as a proxy to DA server 106 . While only two user devices 104 and 122 are shown in FIG. 1 , it should be appreciated that system 100 can include any number and type of user devices configured in this proxy configuration to communicate with DA server system 106 .
- the digital assistant shown in FIG. 1 can include both a client-side portion (e.g., DA client 102 ) and a server-side portion (e.g., DA server 106 ), in some examples, the functions of a digital assistant can be implemented as a standalone application installed on a user device. In addition, the divisions of functionalities between the client and server portions of the digital assistant can vary in different implementations. For instance, in some examples, the DA client can be a thin-client that provides only user-facing input and output processing functions, and delegates all other functionalities of the digital assistant to a backend server.
- FIG. 2A is a block diagram illustrating portable multifunction device 200 with touch-sensitive display system 212 in accordance with some embodiments.
- Touch-sensitive display 212 is sometimes called a “touch screen” for convenience and is sometimes known as or called a “touch-sensitive display system.”
- Device 200 includes memory 202 (which optionally includes one or more computer-readable storage mediums), memory controller 222 , one or more processing units (CPUs) 220 , peripherals interface 218 , RF circuitry 208 , audio circuitry 210 , speaker 211 , microphone 213 , input/output (I/O) subsystem 206 , other input control devices 216 , and external port 224 .
- memory 202 which optionally includes one or more computer-readable storage mediums
- memory controller 222 includes one or more processing units (CPUs) 220 , peripherals interface 218 , RF circuitry 208 , audio circuitry 210 , speaker 211 , microphone 213 , input/output (I/O) subsystem
- Device 200 optionally includes one or more optical sensors 264 .
- Device 200 optionally includes one or more contact intensity sensors 265 for detecting intensity of contacts on device 200 (e.g., a touch-sensitive surface such as touch-sensitive display system 212 of device 200 ).
- Device 200 optionally includes one or more tactile output generators 267 for generating tactile outputs on device 200 (e.g., generating tactile outputs on a touch-sensitive surface such as touch-sensitive display system 212 of device 200 or touchpad 455 of device 400 ).
- These components optionally communicate over one or more communication buses or signal lines 203 .
- the term “intensity” of a contact on a touch-sensitive surface refers to the force or pressure (force per unit area) of a contact (e.g., a finger contact) on the touch-sensitive surface, or to a substitute (proxy) for the force or pressure of a contact on the touch-sensitive surface.
- the intensity of a contact has a range of values that includes at least four distinct values and more typically includes hundreds of distinct values (e.g., at least 256).
- Intensity of a contact is, optionally, determined (or measured) using various approaches and various sensors or combinations of sensors. For example, one or more force sensors underneath or adjacent to the touch-sensitive surface are, optionally, used to measure force at various points on the touch-sensitive surface.
- force measurements from multiple force sensors are combined (e.g., a weighted average) to determine an estimated force of a contact.
- a pressure-sensitive tip of a stylus is, optionally, used to determine a pressure of the stylus on the touch-sensitive surface.
- the size of the contact area detected on the touch-sensitive surface and/or changes thereto, the capacitance of the touch-sensitive surface proximate to the contact and/or changes thereto, and/or the resistance of the touch-sensitive surface proximate to the contact and/or changes thereto are, optionally, used as a substitute for the force or pressure of the contact on the touch-sensitive surface.
- the substitute measurements for contact force or pressure are used directly to determine whether an intensity threshold has been exceeded (e.g., the intensity threshold is described in units corresponding to the substitute measurements).
- the substitute measurements for contact force or pressure are converted to an estimated force or pressure, and the estimated force or pressure is used to determine whether an intensity threshold has been exceeded (e.g., the intensity threshold is a pressure threshold measured in units of pressure).
- intensity of a contact as an attribute of a user input allows for user access to additional device functionality that may otherwise not be accessible by the user on a reduced-size device with limited real estate for displaying affordances (e.g., on a touch-sensitive display) and/or receiving user input (e.g., via a touch-sensitive display, a touch-sensitive surface, or a physical/mechanical control such as a knob or a button).
- the term “tactile output” refers to physical displacement of a device relative to a previous position of the device, physical displacement of a component (e.g., a touch-sensitive surface) of a device relative to another component (e.g., housing) of the device, or displacement of the component relative to a center of mass of the device that will be detected by a user with the user's sense of touch.
- a component e.g., a touch-sensitive surface
- another component e.g., housing
- the tactile output generated by the physical displacement will be interpreted by the user as a tactile sensation corresponding to a perceived change in physical characteristics of the device or the component of the device.
- a touch-sensitive surface e.g., a touch-sensitive display or trackpad
- the user is, optionally, interpreted by the user as a “down click” or “up click” of a physical actuator button.
- a user will feel a tactile sensation such as an “down click” or “up click” even when there is no movement of a physical actuator button associated with the touch-sensitive surface that is physically pressed (e.g., displaced) by the user's movements.
- movement of the touch-sensitive surface is, optionally, interpreted or sensed by the user as “roughness” of the touch-sensitive surface, even when there is no change in smoothness of the touch-sensitive surface. While such interpretations of touch by a user will be subject to the individualized sensory perceptions of the user, there are many sensory perceptions of touch that are common to a large majority of users.
- a tactile output is described as corresponding to a particular sensory perception of a user (e.g., an “up click,” a “down click,” “roughness”)
- the generated tactile output corresponds to physical displacement of the device or a component thereof that will generate the described sensory perception for a typical (or average) user.
- device 200 is only one example of a portable multifunction device, and that device 200 optionally has more or fewer components than shown, optionally combines two or more components, or optionally has a different configuration or arrangement of the components.
- the various components shown in FIG. 2A are implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and/or application-specific integrated circuits.
- Memory 202 may include one or more computer-readable storage mediums.
- the computer-readable storage mediums may be tangible and non-transitory.
- Memory 202 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices.
- Memory controller 222 may control access to memory 202 by other components of device 200 .
- a non-transitory computer-readable storage medium of memory 202 can be used to store instructions (e.g., for performing aspects of process 900 , described below) for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
- the instructions e.g., for performing aspects of process 900 , described below
- a “non-transitory computer-readable storage medium” can be any medium that can contain or store the program for use by or in connection with the instruction execution system, apparatus, or device.
- Peripherals interface 218 can be used to couple input and output peripherals of the device to CPU 220 and memory 202 .
- the one or more processors 220 run or execute various software programs and/or sets of instructions stored in memory 202 to perform various functions for device 200 and to process data.
- peripherals interface 218 , CPU 220 , and memory controller 222 may be implemented on a single chip, such as chip 204 . In some other embodiments, they may be implemented on separate chips.
- RF (radio frequency) circuitry 208 receives and sends RF signals, also called electromagnetic signals.
- RF circuitry 208 converts electrical signals to/from electromagnetic signals and communicates with communications networks and other communications devices via the electromagnetic signals.
- RF circuitry 208 optionally includes well-known circuitry for performing these functions, including but not limited to an antenna system, an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a CODEC chipset, a subscriber identity module (SIM) card, memory, and so forth.
- an antenna system an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a CODEC chipset, a subscriber identity module (SIM) card, memory, and so forth.
- SIM subscriber identity module
- RF circuitry 208 optionally communicates with networks, such as the Internet, also referred to as the World Wide Web (WWW), an intranet and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN) and/or a metropolitan area network (MAN), and other devices by wireless communication.
- the RF circuitry 208 optionally includes well-known circuitry for detecting near field communication (NFC) fields, such as by a short-range communication radio.
- NFC near field communication
- the wireless communication optionally uses any of a plurality of communications standards, protocols, and technologies, including but not limited to Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), high-speed downlink packet access (HSDPA), high-speed uplink packet access (HSUPA), Evolution, Data-Only (EV-DO), HSPA, HSPA+, Dual-Cell HSPA (DC-HSPDA), long term evolution (LTE), near field communication (NFC), wideband code division multiple access (W-CDMA), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Bluetooth Low Energy (BTLE), Wireless Fidelity (Wi-Fi) (e.g., IEEE 802.11a, IEEE 802.11b, IEEE 802.11g, IEEE 802.11n, and/or IEEE 802.11ac), voice over Internet Protocol (VoIP), Wi-MAX, a protocol for e mail (e.g., Internet message access protocol (IMAP) and/or post office protocol (POP)), instant messaging (e.g
- Audio circuitry 210 , speaker 211 , and microphone 213 provide an audio interface between a user and device 200 .
- Audio circuitry 210 receives audio data from peripherals interface 218 , converts the audio data to an electrical signal, and transmits the electrical signal to speaker 211 .
- Speaker 211 converts the electrical signal to human-audible sound waves.
- Audio circuitry 210 also receives electrical signals converted by microphone 213 from sound waves. Audio circuitry 210 converts the electrical signal to audio data and transmits the audio data to peripherals interface 218 for processing. Audio data may be retrieved from and/or transmitted to memory 202 and/or RF circuitry 208 by peripherals interface 218 .
- audio circuitry 210 also includes a headset jack (e.g., 312 , FIG. 3 ).
- the headset jack provides an interface between audio circuitry 210 and removable audio input/output peripherals, such as output-only headphones or a headset with both output (e.g., a headphone for one or both ears) and input (e.g., a microphone).
- I/O subsystem 206 couples input/output peripherals on device 200 , such as touch screen 212 and other input control devices 216 , to peripherals interface 218 .
- I/O subsystem 206 optionally includes display controller 256 , optical sensor controller 258 , intensity sensor controller 259 , haptic feedback controller 261 , and one or more input controllers 260 for other input or control devices.
- the one or more input controllers 260 receive/send electrical signals from/to other input control devices 216 .
- the other input control devices 216 optionally include physical buttons (e.g., push buttons, rocker buttons, etc.), dials, slider switches, joysticks, click wheels, and so forth.
- input controller(s) 260 are, optionally, coupled to any (or none) of the following: a keyboard, an infrared port, a USB port, and a pointer device such as a mouse.
- the one or more buttons optionally include an up/down button for volume control of speaker 211 and/or microphone 213 .
- the one or more buttons optionally include a push button (e.g., 306 , FIG. 3 ).
- a quick press of the push button may disengage a lock of touch screen 212 or begin a process that uses gestures on the touch screen to unlock the device, as described in U.S. patent application Ser. No. 11/322,549, “Unlocking a Device by Performing Gestures on an Unlock Image,” filed Dec. 23, 2005, U.S. Pat. No. 7,657,849, which is hereby incorporated by reference in its entirety.
- a longer press of the push button (e.g., 306 ) may turn power to device 200 on or off.
- the user may be able to customize a functionality of one or more of the buttons.
- Touch screen 212 is used to implement virtual or soft buttons and one or more soft keyboards.
- Touch-sensitive display 212 provides an input interface and an output interface between the device and a user.
- Display controller 256 receives and/or sends electrical signals from/to touch screen 212 .
- Touch screen 212 displays visual output to the user.
- the visual output may include graphics, text, icons, video, and any combination thereof (collectively termed “graphics”). In some embodiments, some or all of the visual output may correspond to user-interface objects.
- Touch screen 212 has a touch-sensitive surface, sensor, or set of sensors that accepts input from the user based on haptic and/or tactile contact.
- Touch screen 212 and display controller 256 (along with any associated modules and/or sets of instructions in memory 202 ) detect contact (and any movement or breaking of the contact) on touch screen 212 and convert the detected contact into interaction with user-interface objects (e.g., one or more soft keys, icons, web pages, or images) that are displayed on touch screen 212 .
- user-interface objects e.g., one or more soft keys, icons, web pages, or images
- a point of contact between touch screen 212 and the user corresponds to a finger of the user.
- Touch screen 212 may use LCD (liquid crystal display) technology, LPD (light emitting polymer display) technology, or LED (light emitting diode) technology, although other display technologies may be used in other embodiments.
- Touch screen 212 and display controller 256 may detect contact and any movement or breaking thereof using any of a plurality of touch sensing technologies now known or later developed, including but not limited to capacitive, resistive, infrared, and surface acoustic wave technologies, as well as other proximity sensor arrays or other elements for determining one or more points of contact with touch screen 212 .
- projected mutual capacitance sensing technology is used, such as that found in the iPhone® and iPod Touch® from Apple Inc. of Cupertino, Calif.
- a touch-sensitive display in some embodiments of touch screen 212 may be analogous to the multi-touch sensitive touchpads described in the following U.S. Pat. No. 6,323,846 (Westerman et al.), U.S. Pat. No. 6,570,557 (Westerman et al.), and/or U.S. Pat. No. 6,677,932 (Westerman), and/or U.S. Patent Publication 2002/0015024A1, each of which is hereby incorporated by reference in its entirety.
- touch screen 212 displays visual output from device 200 , whereas touch-sensitive touchpads do not provide visual output.
- a touch-sensitive display in some embodiments of touch screen 212 may be as described in the following applications: (1) U.S. patent application Ser. No. 11/381,313, “Multipoint Touch Surface Controller,” filed May 2, 2006; (2) U.S. patent application Ser. No. 10/840,862, “Multipoint Touchscreen,” filed May 6, 2004; (3) U.S. patent application Ser. No. 10/903,964, “Gestures For Touch Sensitive Input Devices,” filed Jul. 30, 2004; (4) U.S. patent application Ser. No. 11/048,264, “Gestures For Touch Sensitive Input Devices,” filed Jan. 31, 2005; (5) U.S. patent application Ser. No.
- Touch screen 212 may have a video resolution in excess of 100 dpi. In some embodiments, the touch screen has a video resolution of approximately 160 dpi.
- the user may make contact with touch screen 212 using any suitable object or appendage, such as a stylus, a finger, and so forth.
- the user interface is designed to work primarily with finger-based contacts and gestures, which can be less precise than stylus-based input due to the larger area of contact of a finger on the touch screen.
- the device translates the rough finger-based input into a precise pointer/cursor position or command for performing the actions desired by the user.
- device 200 may include a touchpad (not shown) for activating or deactivating particular functions.
- the touchpad is a touch-sensitive area of the device that, unlike the touch screen, does not display visual output.
- the touchpad may be a touch-sensitive surface that is separate from touch screen 212 or an extension of the touch-sensitive surface formed by the touch screen.
- Power system 262 for powering the various components.
- Power system 262 may include a power management system, one or more power sources (e.g., battery, alternating current (AC)), a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator (e.g., a light-emitting diode (LED)) and any other components associated with the generation, management and distribution of power in portable devices.
- power sources e.g., battery, alternating current (AC)
- AC alternating current
- a recharging system e.g., a recharging system
- a power failure detection circuit e.g., a power failure detection circuit
- a power converter or inverter e.g., a power converter or inverter
- a power status indicator e.g., a light-emitting diode (LED)
- Device 200 may also include one or more optical sensors 264 .
- FIG. 2A shows an optical sensor coupled to optical sensor controller 258 in I/O subsystem 206 .
- Optical sensor 264 may include charge-coupled device (CCD) or complementary metal-oxide semiconductor (CMOS) phototransistors.
- CMOS complementary metal-oxide semiconductor
- Optical sensor 264 receives light from the environment, projected through one or more lenses, and converts the light to data representing an image.
- imaging module 243 also called a camera module
- optical sensor 264 may capture still images or video.
- an optical sensor is located on the back of device 200 , opposite touch screen display 212 on the front of the device so that the touch screen display may be used as a viewfinder for still and/or video image acquisition.
- an optical sensor is located on the front of the device so that the user's image may be obtained for video conferencing while the user views the other video conference participants on the touch screen display.
- the position of optical sensor 264 can be changed by the user (e.g., by rotating the lens and the sensor in the device housing) so that a single optical sensor 264 may be used along with the touch screen display for both video conferencing and still and/or video image acquisition.
- Device 200 optionally also includes one or more contact intensity sensors 265 .
- FIG. 2A shows a contact intensity sensor coupled to intensity sensor controller 259 in I/O subsystem 206 .
- Contact intensity sensor 265 optionally includes one or more piezoresistive strain gauges, capacitive force sensors, electric force sensors, piezoelectric force sensors, optical force sensors, capacitive touch-sensitive surfaces, or other intensity sensors (e.g., sensors used to measure the force (or pressure) of a contact on a touch-sensitive surface).
- Contact intensity sensor 265 receives contact intensity information (e.g., pressure information or a proxy for pressure information) from the environment.
- contact intensity information e.g., pressure information or a proxy for pressure information
- At least one contact intensity sensor is collocated with, or proximate to, a touch-sensitive surface (e.g., touch-sensitive display system 212 ). In some embodiments, at least one contact intensity sensor is located on the back of device 200 , opposite touch screen display 212 , which is located on the front of device 200 .
- Device 200 may also include one or more proximity sensors 266 .
- FIG. 2A shows proximity sensor 266 coupled to peripherals interface 218 .
- proximity sensor 266 may be coupled to input controller 260 in I/O subsystem 206 .
- Proximity sensor 266 may perform as described in U.S. patent application Ser. No. 11/241,839, “Proximity Detector In Handheld Device”; Ser. No. 11/240,788, “Proximity Detector In Handheld Device”; Ser. No. 11/620,702, “Using Ambient Light Sensor To Augment Proximity Sensor Output”; Ser. No. 11/586,862, “Automated Response To And Sensing Of User Activity In Portable Devices”; and Ser. No.
- the proximity sensor turns off and disables touch screen 212 when the multifunction device is placed near the user's ear (e.g., when the user is making a phone call).
- Device 200 optionally also includes one or more tactile output generators 267 .
- FIG. 2A shows a tactile output generator coupled to haptic feedback controller 261 in I/O subsystem 206 .
- Tactile output generator 267 optionally includes one or more electroacoustic devices such as speakers or other audio components and/or electromechanical devices that convert energy into linear motion such as a motor, solenoid, electroactive polymer, piezoelectric actuator, electrostatic actuator, or other tactile output generating component (e.g., a component that converts electrical signals into tactile outputs on the device).
- Contact intensity sensor 265 receives tactile feedback generation instructions from haptic feedback module 233 and generates tactile outputs on device 200 that are capable of being sensed by a user of device 200 .
- At least one tactile output generator is collocated with, or proximate to, a touch-sensitive surface (e.g., touch-sensitive display system 212 ) and, optionally, generates a tactile output by moving the touch-sensitive surface vertically (e.g., in/out of a surface of device 200 ) or laterally (e.g., back and forth in the same plane as a surface of device 200 ).
- at least one tactile output generator sensor is located on the back of device 200 , opposite touch screen display 212 , which is located on the front of device 200 .
- Device 200 may also include one or more accelerometers 268 .
- FIG. 2A shows accelerometer 268 coupled to peripherals interface 218 .
- accelerometer 268 may be coupled to an input controller 260 in I/O subsystem 206 .
- Accelerometer 268 may perform as described in U.S. Patent Publication No. 20050190059, “Acceleration-based Theft Detection System for Portable Electronic Devices,” and U.S. Patent Publication No. 20060017692, “Methods And Apparatuses For Operating A Portable Device Based On An Accelerometer,” both of which are incorporated by reference herein in their entirety.
- information is displayed on the touch screen display in a portrait view or a landscape view based on an analysis of data received from the one or more accelerometers.
- Device 200 optionally includes, in addition to accelerometer(s) 268 , a magnetometer (not shown) and a GPS (or GLONASS or other global navigation system) receiver (not shown) for obtaining information concerning the location and orientation (e.g., portrait or landscape) of device 200 .
- the software components stored in memory 202 include operating system 226 , communication module (or set of instructions) 228 , contact/motion module (or set of instructions) 230 , graphics module (or set of instructions) 232 , text input module (or set of instructions) 234 , Global Positioning System (GPS) module (or set of instructions) 235 , Digital Assistant Client Module 229 , and applications (or sets of instructions) 236 .
- memory 202 can store data and models, such as user data and models 231 .
- memory 202 ( FIG. 2A ) or 470 ( FIG. 4 ) stores device/global internal state 257 , as shown in FIGS. 2A and 4 .
- Device/global internal state 257 includes one or more of: active application state, indicating which applications, if any, are currently active; display state, indicating what applications, views or other information occupy various regions of touch screen display 212 ; sensor state, including information obtained from the device's various sensors and input control devices 216 ; and location information concerning the device's location and/or attitude.
- Operating system 226 e.g., Darwin, RTXC, LINUX, UNIX, OS X, iOS, WINDOWS, or an embedded operating system such as VxWorks
- Operating system 226 includes various software components and/or drivers for controlling and managing general system tasks (e.g., memory management, storage device control, power management, etc.) and facilitates communication between various hardware and software components.
- Communication module 228 facilitates communication with other devices over one or more external ports 224 and also includes various software components for handling data received by RF circuitry 208 and/or external port 224 .
- External port 224 e.g., Universal Serial Bus (USB), FIREWIRE, etc.
- USB Universal Serial Bus
- FIREWIRE FireWire
- the external port is a multi-pin (e.g., 30-pin) connector that is the same as, or similar to and/or compatible with, the 30-pin connector used on iPod® (trademark of Apple Inc.) devices.
- Contact/motion module 230 optionally detects contact with touch screen 212 (in conjunction with display controller 256 ) and other touch-sensitive devices (e.g., a touchpad or physical click wheel).
- Contact/motion module 230 includes various software components for performing various operations related to detection of contact, such as determining if contact has occurred (e.g., detecting a finger-down event), determining an intensity of the contact (e.g., the force or pressure of the contact or a substitute for the force or pressure of the contact), determining if there is movement of the contact and tracking the movement across the touch-sensitive surface (e.g., detecting one or more finger-dragging events), and determining if the contact has ceased (e.g., detecting a finger-up event or a break in contact).
- Contact/motion module 230 receives contact data from the touch-sensitive surface. Determining movement of the point of contact, which is represented by a series of contact data, optionally includes determining speed (magnitude), velocity (magnitude and direction), and/or an acceleration (a change in magnitude and/or direction) of the point of contact. These operations are, optionally, applied to single contacts (e.g., one finger contacts) or to multiple simultaneous contacts (e.g., “multitouch”/multiple finger contacts). In some embodiments, contact/motion module 230 and display controller 256 detect contact on a touchpad.
- contact/motion module 230 uses a set of one or more intensity thresholds to determine whether an operation has been performed by a user (e.g., to determine whether a user has “clicked” on an icon).
- at least a subset of the intensity thresholds are determined in accordance with software parameters (e.g., the intensity thresholds are not determined by the activation thresholds of particular physical actuators and can be adjusted without changing the physical hardware of device 200 ). For example, a mouse “click” threshold of a trackpad or touch screen display can be set to any of a large range of predefined threshold values without changing the trackpad or touch screen display hardware.
- a user of the device is provided with software settings for adjusting one or more of the set of intensity thresholds (e.g., by adjusting individual intensity thresholds and/or by adjusting a plurality of intensity thresholds at once with a system-level click “intensity” parameter).
- Contact/motion module 230 optionally detects a gesture input by a user.
- Different gestures on the touch-sensitive surface have different contact patterns (e.g., different motions, timings, and/or intensities of detected contacts).
- a gesture is, optionally, detected by detecting a particular contact pattern.
- detecting a finger tap gesture includes detecting a finger-down event followed by detecting a finger-up (liftoff) event at the same position (or substantially the same position) as the finger-down event (e.g., at the position of an icon).
- detecting a finger swipe gesture on the touch-sensitive surface includes detecting a finger-down event followed by detecting one or more finger-dragging events, and subsequently followed by detecting a finger-up (liftoff) event.
- Graphics module 232 includes various known software components for rendering and displaying graphics on touch screen 212 or other display, including components for changing the visual impact (e.g., brightness, transparency, saturation, contrast, or other visual property) of graphics that are displayed.
- graphics includes any object that can be displayed to a user, including, without limitation, text, web pages, icons (such as user-interface objects including soft keys), digital images, videos, animations, and the like.
- graphics module 232 stores data representing graphics to be used. Each graphic is, optionally, assigned a corresponding code. Graphics module 232 receives, from applications etc., one or more codes specifying graphics to be displayed along with, if necessary, coordinate data and other graphic property data, and then generates screen image data to output to display controller 256 .
- Haptic feedback module 233 includes various software components for generating instructions used by tactile output generator(s) 267 to produce tactile outputs at one or more locations on device 200 in response to user interactions with device 200 .
- Text input module 234 which may be a component of graphics module 232 , provides soft keyboards for entering text in various applications (e.g., contacts 237 , e mail 240 , IM 241 , browser 247 , and any other application that needs text input).
- applications e.g., contacts 237 , e mail 240 , IM 241 , browser 247 , and any other application that needs text input).
- GPS module 235 determines the location of the device and provides this information for use in various applications (e.g., to telephone 238 for use in location-based dialing; to camera 243 as picture/video metadata; and to applications that provide location-based services such as weather widgets, local yellow page widgets, and map/navigation widgets).
- applications e.g., to telephone 238 for use in location-based dialing; to camera 243 as picture/video metadata; and to applications that provide location-based services such as weather widgets, local yellow page widgets, and map/navigation widgets).
- Digital assistant client module 229 can include various client-side digital assistant instructions to provide the client-side functionalities of the digital assistant.
- digital assistant client module 229 can be capable of accepting voice input (e.g., speech input), text input, touch input, and/or gestural input through various user interfaces (e.g., microphone 213 , accelerometer(s) 268 , touch-sensitive display system 212 , optical sensor(s) 229 , other input control devices 216 , etc.) of portable multifunction device 200 .
- Digital assistant client module 229 can also be capable of providing output in audio (e.g., speech output), visual, and/or tactile forms through various output interfaces (e.g., speaker 211 , touch-sensitive display system 212 , tactile output generator(s) 267 , etc.) of portable multifunction device 200 .
- output can be provided as voice, sound, alerts, text messages, menus, graphics, videos, animations, vibrations, and/or combinations of two or more of the above.
- digital assistant client module 229 can communicate with DA server 106 using RF circuitry 208 .
- User data and models 231 can include various data associated with the user (e.g., user-specific vocabulary data, user preference data, user-specified name pronunciations, data from the user's electronic address book, to-do lists, shopping lists, etc.) to provide the client-side functionalities of the digital assistant. Further, user data and models 231 can includes various models (e.g., speech recognition models, statistical language models, natural language processing models, ontology, task flow models, service models, etc.) for processing user input and determining user intent.
- various models e.g., speech recognition models, statistical language models, natural language processing models, ontology, task flow models, service models, etc.
- digital assistant client module 229 can utilize the various sensors, subsystems, and peripheral devices of portable multifunction device 200 to gather additional information from the surrounding environment of the portable multifunction device 200 to establish a context associated with a user, the current user interaction, and/or the current user input.
- digital assistant client module 229 can provide the contextual information or a subset thereof with the user input to DA server 106 to help infer the user's intent.
- the digital assistant can also use the contextual information to determine how to prepare and deliver outputs to the user. Contextual information can be referred to as context data.
- the contextual information that accompanies the user input can include sensor information, e.g., lighting, ambient noise, ambient temperature, images or videos of the surrounding environment, etc.
- the contextual information can also include the physical state of the device, e.g., device orientation, device location, device temperature, power level, speed, acceleration, motion patterns, cellular signals strength, etc.
- information related to the software state of DA server 106 e.g., running processes, installed programs, past and present network activities, background services, error logs, resources usage, etc., and of portable multifunction device 200 can be provided to DA server 106 as contextual information associated with a user input.
- the digital assistant client module 229 can selectively provide information (e.g., user data 231 ) stored on the portable multifunction device 200 in response to requests from DA server 106 .
- digital assistant client module 229 can also elicit additional input from the user via a natural language dialogue or other user interfaces upon request by DA server 106 .
- Digital assistant client module 229 can pass the additional input to DA server 106 to help DA server 106 in intent deduction and/or fulfillment of the user's intent expressed in the user request.
- digital assistant client module 229 can include any number of the sub-modules of digital assistant module 726 described below.
- Applications 236 may include the following modules (or sets of instructions), or a subset or superset thereof:
- Examples of other applications 236 that may be stored in memory 202 include other word processing applications, other image editing applications, drawing applications, presentation applications, JAVA-enabled applications, encryption, digital rights management, voice recognition, and voice replication.
- contacts module 237 may be used to manage an address book or contact list (e.g., stored in application internal state 292 of contacts module 237 in memory 202 or memory 470 ), including: adding name(s) to the address book; deleting name(s) from the address book; associating telephone number(s), e-mail address(es), physical address(es) or other information with a name; associating an image with a name; categorizing and sorting names; providing telephone numbers or e-mail addresses to initiate and/or facilitate communications by telephone 238 , video conference module 239 , e-mail 240 , or IM 241 ; and so forth.
- an address book or contact list e.g., stored in application internal state 292 of contacts module 237 in memory 202 or memory 470 , including: adding name(s) to the address book; deleting name(s) from the address book; associating telephone number(s), e-mail address(es), physical address(es) or other information with a name; as
- telephone module 238 may be used to enter a sequence of characters corresponding to a telephone number, access one or more telephone numbers in contacts module 237 , modify a telephone number that has been entered, dial a respective telephone number, conduct a conversation, and disconnect or hang up when the conversation is completed.
- the wireless communication may use any of a plurality of communications standards, protocols, and technologies.
- video conference module 239 includes executable instructions to initiate, conduct, and terminate a video conference between a user and one or more other participants in accordance with user instructions.
- e-mail client module 240 includes executable instructions to create, send, receive, and manage e-mail in response to user instructions.
- e-mail client module 240 makes it very easy to create and send e-mails with still or video images taken with camera module 243 .
- the instant messaging module 241 includes executable instructions to enter a sequence of characters corresponding to an instant message, to modify previously entered characters, to transmit a respective instant message (for example, using a Short Message Service (SMS) or Multimedia Message Service (MMS) protocol for telephony-based instant messages or using XMPP, SIMPLE, or IMPS for Internet-based instant messages), to receive instant messages, and to view received instant messages.
- SMS Short Message Service
- MMS Multimedia Message Service
- XMPP extensible Markup Language
- SIMPLE Session Initiation Protocol
- IMPS Internet Messaging Protocol
- transmitted and/or received instant messages may include graphics, photos, audio files, video files and/or other attachments as are supported in an MMS and/or an Enhanced Messaging Service (EMS).
- EMS Enhanced Messaging Service
- instant messaging refers to both telephony-based messages (e.g., messages sent using SMS or MMS) and Internet-based messages (e.g., messages sent using XMPP, SIMPLE, or IMPS).
- workout support module 242 includes executable instructions to create workouts (e.g., with time, distance, and/or calorie burning goals); communicate with workout sensors (sports devices); receive workout sensor data; calibrate sensors used to monitor a workout; select and play music for a workout; and display, store, and transmit workout data.
- create workouts e.g., with time, distance, and/or calorie burning goals
- communicate with workout sensors sports devices
- receive workout sensor data calibrate sensors used to monitor a workout
- select and play music for a workout and display, store, and transmit workout data.
- camera module 243 includes executable instructions to capture still images or video (including a video stream) and store them into memory 202 , modify characteristics of a still image or video, or delete a still image or video from memory 202 .
- image management module 244 includes executable instructions to arrange, modify (e.g., edit), or otherwise manipulate, label, delete, present (e.g., in a digital slide show or album), and store still and/or video images.
- modify e.g., edit
- present e.g., in a digital slide show or album
- browser module 247 includes executable instructions to browse the Internet in accordance with user instructions, including searching, linking to, receiving, and displaying web pages or portions thereof, as well as attachments and other files linked to web pages.
- calendar module 248 includes executable instructions to create, display, modify, and store calendars and data associated with calendars (e.g., calendar entries, to-do lists, etc.) in accordance with user instructions.
- widget modules 249 are mini-applications that may be downloaded and used by a user (e.g., weather widget 249 - 1 , stocks widget 249 - 2 , calculator widget 249 - 3 , alarm clock widget 249 - 4 , and dictionary widget 249 - 5 ) or created by the user (e.g., user-created widget 249 - 6 ).
- a widget includes an HTML (Hypertext Markup Language) file, a CSS (Cascading Style Sheets) file, and a JavaScript file.
- a widget includes an XML (Extensible Markup Language) file and a JavaScript file (e.g., Yahoo! Widgets).
- the widget creator module 250 may be used by a user to create widgets (e.g., turning a user-specified portion of a web page into a widget).
- search module 251 includes executable instructions to search for text, music, sound, image, video, and/or other files in memory 202 that match one or more search criteria (e.g., one or more user-specified search terms) in accordance with user instructions.
- search criteria e.g., one or more user-specified search terms
- video and music player module 252 includes executable instructions that allow the user to download and play back recorded music and other sound files stored in one or more file formats, such as MP3 or AAC files, and executable instructions to display, present, or otherwise play back videos (e.g., on touch screen 212 or on an external, connected display via external port 224 ).
- device 200 optionally includes the functionality of an MP3 player, such as an iPod (trademark of Apple Inc.).
- notes module 253 includes executable instructions to create and manage notes, to-do lists, and the like in accordance with user instructions.
- map module 254 may be used to receive, display, modify, and store maps and data associated with maps (e.g., driving directions, data on stores and other points of interest at or near a particular location, and other location-based data) in accordance with user instructions.
- maps e.g., driving directions, data on stores and other points of interest at or near a particular location, and other location-based data
- online video module 255 includes instructions that allow the user to access, browse, receive (e.g., by streaming and/or download), play back (e.g., on the touch screen or on an external, connected display via external port 224 ), send an e-mail with a link to a particular online video, and otherwise manage online videos in one or more file formats, such as H.264.
- instant messaging module 241 is used to send a link to a particular online video. Additional description of the online video application can be found in U.S. Provisional Patent Application No. 60/936,562, “Portable Multifunction Device, Method, and Graphical User Interface for Playing Online Videos,” filed Jun. 20, 2007, and U.S. patent application Ser. No. 11/968,067, “Portable Multifunction Device, Method, and Graphical User Interface for Playing Online Videos,” filed Dec. 31, 2007, the contents of which are hereby incorporated by reference in their entirety.
- modules and applications corresponds to a set of executable instructions for performing one or more functions described above and the methods described in this application (e.g., the computer-implemented methods and other information processing methods described herein).
- modules e.g., sets of instructions
- video player module may be combined with music player module into a single module (e.g., video and music player module 252 , FIG. 2A ).
- memory 202 may store a subset of the modules and data structures identified above.
- memory 202 may store additional modules and data structures not described above.
- device 200 is a device where operation of a predefined set of functions on the device is performed exclusively through a touch screen and/or a touchpad.
- a touch screen and/or a touchpad as the primary input control device for operation of device 200 , the number of physical input control devices (such as push buttons, dials, and the like) on device 200 may be reduced.
- the predefined set of functions that are performed exclusively through a touch screen and/or a touchpad optionally include navigation between user interfaces.
- the touchpad when touched by the user, navigates device 200 to a main, home, or root menu from any user interface that is displayed on device 200 .
- a “menu button” is implemented using a touchpad.
- the menu button is a physical push button or other physical input control device instead of a touchpad.
- FIG. 2B is a block diagram illustrating exemplary components for event handling in accordance with some embodiments.
- memory 202 FIG. 2A
- 470 FIG. 4
- memory 202 FIG. 2A
- 470 FIG. 4
- event sorter 270 e.g., in operating system 226
- application 236 - 1 e.g., any of the aforementioned applications 237 - 251 , 255 , 480 - 490 .
- Event sorter 270 receives event information and determines the application 236 - 1 and application view 291 of application 236 - 1 to which to deliver the event information.
- Event sorter 270 includes event monitor 271 and event dispatcher module 274 .
- application 236 - 1 includes application internal state 292 , which indicates the current application view(s) displayed on touch-sensitive display 212 when the application is active or executing.
- device/global internal state 257 is used by event sorter 270 to determine which application(s) is (are) currently active, and application internal state 292 is used by event sorter 270 to determine application views 291 to which to deliver event information.
- application internal state 292 includes additional information, such as one or more of: resume information to be used when application 236 - 1 resumes execution, user interface state information that indicates information being displayed or that is ready for display by application 236 - 1 , a state queue for enabling the user to go back to a prior state or view of application 236 - 1 , and a redo/undo queue of previous actions taken by the user.
- Event monitor 271 receives event information from peripherals interface 218 .
- Event information includes information about a sub-event (e.g., a user touch on touch-sensitive display 212 , as part of a multi-touch gesture).
- Peripherals interface 218 transmits information it receives from I/O subsystem 206 or a sensor, such as proximity sensor 266 , accelerometer(s) 268 , and/or microphone 213 (through audio circuitry 210 ).
- Information that peripherals interface 218 receives from I/O subsystem 206 includes information from touch-sensitive display 212 or a touch-sensitive surface.
- event monitor 271 sends requests to the peripherals interface 218 at predetermined intervals. In response, peripherals interface 218 transmits event information. In other embodiments, peripherals interface 218 transmits event information only when there is a significant event (e.g., receiving an input above a predetermined noise threshold and/or for more than a predetermined duration).
- event sorter 270 also includes a hit view determination module 272 and/or an active event recognizer determination module 273 .
- Hit view determination module 272 provides software procedures for determining where a sub-event has taken place within one or more views when touch-sensitive display 212 displays more than one view. Views are made up of controls and other elements that a user can see on the display.
- the application views (of a respective application) in which a touch is detected may correspond to programmatic levels within a programmatic or view hierarchy of the application. For example, the lowest level view in which a touch is detected may be called the hit view, and the set of events that are recognized as proper inputs may be determined based, at least in part, on the hit view of the initial touch that begins a touch-based gesture.
- Hit view determination module 272 receives information related to sub events of a touch-based gesture.
- hit view determination module 272 identifies a hit view as the lowest view in the hierarchy which should handle the sub-event. In most circumstances, the hit view is the lowest level view in which an initiating sub-event occurs (e.g., the first sub-event in the sequence of sub-events that form an event or potential event).
- the hit view typically receives all sub-events related to the same touch or input source for which it was identified as the hit view.
- Active event recognizer determination module 273 determines which view or views within a view hierarchy should receive a particular sequence of sub-events. In some embodiments, active event recognizer determination module 273 determines that only the hit view should receive a particular sequence of sub-events. In other embodiments, active event recognizer determination module 273 determines that all views that include the physical location of a sub-event are actively involved views, and therefore determines that all actively involved views should receive a particular sequence of sub-events. In other embodiments, even if touch sub-events were entirely confined to the area associated with one particular view, views higher in the hierarchy would still remain as actively involved views.
- Event dispatcher module 274 dispatches the event information to an event recognizer (e.g., event recognizer 280 ). In embodiments including active event recognizer determination module 273 , event dispatcher module 274 delivers the event information to an event recognizer determined by active event recognizer determination module 273 . In some embodiments, event dispatcher module 274 stores in an event queue the event information, which is retrieved by a respective event receiver 282 .
- operating system 226 includes event sorter 270 .
- application 236 - 1 includes event sorter 270 .
- event sorter 270 is a stand-alone module, or a part of another module stored in memory 202 , such as contact/motion module 230 .
- application 236 - 1 includes a plurality of event handlers 290 and one or more application views 291 , each of which includes instructions for handling touch events that occur within a respective view of the application's user interface.
- Each application view 291 of the application 236 - 1 includes one or more event recognizers 280 .
- a respective application view 291 includes a plurality of event recognizers 280 .
- one or more of event recognizers 280 are part of a separate module, such as a user interface kit (not shown) or a higher level object from which application 236 - 1 inherits methods and other properties.
- a respective event handler 290 includes one or more of: data updater 276 , object updater 277 , GUI updater 278 , and/or event data 279 received from event sorter 270 .
- Event handler 290 may utilize or call data updater 276 , object updater 277 , or GUI updater 278 to update the application internal state 292 .
- one or more of the application views 291 include one or more respective event handlers 290 .
- one or more of data updater 276 , object updater 277 , and GUI updater 278 are included in a respective application view 291 .
- a respective event recognizer 280 receives event information (e.g., event data 279 ) from event sorter 270 and identifies an event from the event information.
- Event recognizer 280 includes event receiver 282 and event comparator 284 .
- event recognizer 280 also includes at least a subset of: metadata 283 , and event delivery instructions 288 (which may include sub-event delivery instructions).
- Event receiver 282 receives event information from event sorter 270 .
- the event information includes information about a sub-event, for example, a touch or a touch movement.
- the event information also includes additional information, such as location of the sub-event.
- the event information may also include speed and direction of the sub-event.
- events include rotation of the device from one orientation to another (e.g., from a portrait orientation to a landscape orientation, or vice versa), and the event information includes corresponding information about the current orientation (also called device attitude) of the device.
- Event comparator 284 compares the event information to predefined event or sub-event definitions and, based on the comparison, determines an event or sub event, or determines or updates the state of an event or sub-event.
- event comparator 284 includes event definitions 286 .
- Event definitions 286 contain definitions of events (e.g., predefined sequences of sub-events), for example, event 1 ( 287 - 1 ), event 2 ( 287 - 2 ), and others.
- sub-events in an event ( 287 ) include, for example, touch begin, touch end, touch movement, touch cancellation, and multiple touching.
- the definition for event 1 ( 287 - 1 ) is a double tap on a displayed object.
- the double tap for example, comprises a first touch (touch begin) on the displayed object for a predetermined phase, a first liftoff (touch end) for a predetermined phase, a second touch (touch begin) on the displayed object for a predetermined phase, and a second liftoff (touch end) for a predetermined phase.
- the definition for event 2 ( 287 - 2 ) is a dragging on a displayed object.
- the dragging for example, comprises a touch (or contact) on the displayed object for a predetermined phase, a movement of the touch across touch-sensitive display 212 , and liftoff of the touch (touch end).
- the event also includes information for one or more associated event handlers 290 .
- event definition 287 includes a definition of an event for a respective user-interface object.
- event comparator 284 performs a hit test to determine which user-interface object is associated with a sub-event. For example, in an application view in which three user-interface objects are displayed on touch-sensitive display 212 , when a touch is detected on touch-sensitive display 212 , event comparator 284 performs a hit test to determine which of the three user-interface objects is associated with the touch (sub-event). If each displayed object is associated with a respective event handler 290 , the event comparator uses the result of the hit test to determine which event handler 290 should be activated. For example, event comparator 284 selects an event handler associated with the sub-event and the object triggering the hit test.
- the definition for a respective event ( 287 ) also includes delayed actions that delay delivery of the event information until after it has been determined whether the sequence of sub-events does or does not correspond to the event recognizer's event type.
- a respective event recognizer 280 determines that the series of sub-events do not match any of the events in event definitions 286 , the respective event recognizer 280 enters an event impossible, event failed, or event ended state, after which it disregards subsequent sub-events of the touch-based gesture. In this situation, other event recognizers, if any, that remain active for the hit view continue to track and process sub-events of an ongoing touch-based gesture.
- a respective event recognizer 280 includes metadata 283 with configurable properties, flags, and/or lists that indicate how the event delivery system should perform sub-event delivery to actively involved event recognizers.
- metadata 283 includes configurable properties, flags, and/or lists that indicate how event recognizers may interact, or are enabled to interact, with one another.
- metadata 283 includes configurable properties, flags, and/or lists that indicate whether sub-events are delivered to varying levels in the view or programmatic hierarchy.
- a respective event recognizer 280 activates event handler 290 associated with an event when one or more particular sub-events of an event are recognized.
- a respective event recognizer 280 delivers event information associated with the event to event handler 290 .
- Activating an event handler 290 is distinct from sending (and deferred sending) sub-events to a respective hit view.
- event recognizer 280 throws a flag associated with the recognized event, and event handler 290 associated with the flag catches the flag and performs a predefined process.
- event delivery instructions 288 include sub-event delivery instructions that deliver event information about a sub-event without activating an event handler. Instead, the sub-event delivery instructions deliver event information to event handlers associated with the series of sub-events or to actively involved views. Event handlers associated with the series of sub-events or with actively involved views receive the event information and perform a predetermined process.
- data updater 276 creates and updates data used in application 236 - 1 .
- data updater 276 updates the telephone number used in contacts module 237 , or stores a video file used in video player module.
- object updater 277 creates and updates objects used in application 236 - 1 .
- object updater 277 creates a new user-interface object or updates the position of a user-interface object.
- GUI updater 278 updates the GUI.
- GUI updater 278 prepares display information and sends it to graphics module 232 for display on a touch-sensitive display.
- event handler(s) 290 includes or has access to data updater 276 , object updater 277 , and GUI updater 278 .
- data updater 276 , object updater 277 , and GUI updater 278 are included in a single module of a respective application 236 - 1 or application view 291 . In other embodiments, they are included in two or more software modules.
- event handling of user touches on touch-sensitive displays also applies to other forms of user inputs to operate multifunction devices 200 with input devices, not all of which are initiated on touch screens.
- mouse movement and mouse button presses optionally coordinated with single or multiple keyboard presses or holds; contact movements such as taps, drags, scrolls, etc. on touchpads; pen stylus inputs; movement of the device; oral instructions; detected eye movements; biometric inputs; and/or any combination thereof are optionally utilized as inputs corresponding to sub-events which define an event to be recognized.
- FIG. 3 illustrates a portable multifunction device 200 having a touch screen 212 in accordance with some embodiments.
- the touch screen optionally displays one or more graphics within user interface (UI) 300 .
- UI user interface
- a user is enabled to select one or more of the graphics by making a gesture on the graphics, for example, with one or more fingers 302 (not drawn to scale in the figure) or one or more styluses 303 (not drawn to scale in the figure).
- selection of one or more graphics occurs when the user breaks contact with the one or more graphics.
- the gesture optionally includes one or more taps, one or more swipes (from left to right, right to left, upward and/or downward), and/or a rolling of a finger (from right to left, left to right, upward and/or downward) that has made contact with device 200 .
- inadvertent contact with a graphic does not select the graphic.
- a swipe gesture that sweeps over an application icon optionally does not select the corresponding application when the gesture corresponding to selection is a tap.
- Device 200 may also include one or more physical buttons, such as “home” or menu button 304 .
- menu button 304 may be used to navigate to any application 236 in a set of applications that may be executed on device 200 .
- the menu button is implemented as a soft key in a GUI displayed on touch screen 212 .
- device 200 includes touch screen 212 , menu button 304 , push button 306 for powering the device on/off and locking the device, volume adjustment button(s) 308 , subscriber identity module (SIM) card slot 310 , headset jack 312 , and docking/charging external port 224 .
- Push button 306 is, optionally, used to turn the power on/off on the device by depressing the button and holding the button in the depressed state for a predefined time interval; to lock the device by depressing the button and releasing the button before the predefined time interval has elapsed; and/or to unlock the device or initiate an unlock process.
- device 200 also accepts verbal input for activation or deactivation of some functions through microphone 213 .
- Device 200 also, optionally, includes one or more contact intensity sensors 265 for detecting intensity of contacts on touch screen 212 and/or one or more tactile output generators 267 for generating tactile outputs for a user of device 200 .
- FIG. 4 is a block diagram of an exemplary multifunction device with a display and a touch-sensitive surface in accordance with some embodiments.
- Device 400 need not be portable.
- device 400 is a laptop computer, a desktop computer, a tablet computer, a multimedia player device, a navigation device, an educational device (such as a child's learning toy), a gaming system, or a control device (e.g., a home or industrial controller).
- Device 400 typically includes one or more processing units (CPUs) 410 , one or more network or other communications interfaces 460 , memory 470 , and one or more communication buses 420 for interconnecting these components.
- CPUs processing units
- Communication buses 420 optionally include circuitry (sometimes called a chipset) that interconnects and controls communications between system components.
- Device 400 includes input/output (I/O) interface 430 comprising display 440 , which is typically a touch screen display.
- I/O interface 430 also optionally includes a keyboard and/or mouse (or other pointing device) 450 and touchpad 455 , tactile output generator 457 for generating tactile outputs on device 400 (e.g., similar to tactile output generator(s) 267 described above with reference to FIG. 2A ), sensors 459 (e.g., optical, acceleration, proximity, touch-sensitive, and/or contact intensity sensors similar to contact intensity sensor(s) 265 described above with reference to FIG. 2A ).
- sensors 459 e.g., optical, acceleration, proximity, touch-sensitive, and/or contact intensity sensors similar to contact intensity sensor(s) 265 described above with reference to FIG. 2A ).
- Memory 470 includes high-speed random access memory, such as DRAM, SRAM, DDR RAM, or other random access solid state memory devices; and optionally includes non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid state storage devices. Memory 470 optionally includes one or more storage devices remotely located from CPU(s) 410 . In some embodiments, memory 470 stores programs, modules, and data structures analogous to the programs, modules, and data structures stored in memory 202 of portable multifunction device 200 ( FIG. 2A ), or a subset thereof. Furthermore, memory 470 optionally stores additional programs, modules, and data structures not present in memory 202 of portable multifunction device 200 .
- memory 470 of device 400 optionally stores drawing module 480 , presentation module 482 , word processing module 484 , website creation module 486 , disk authoring module 488 , and/or spreadsheet module 490 , while memory 202 of portable multifunction device 200 ( FIG. 2A ) optionally does not store these modules.
- Each of the above-identified elements in FIG. 4 may be stored in one or more of the previously mentioned memory devices.
- Each of the above-identified modules corresponds to a set of instructions for performing a function described above.
- the above-identified modules or programs (e.g., sets of instructions) need not be implemented as separate software programs, procedures, or modules, and thus various subsets of these modules may be combined or otherwise rearranged in various embodiments.
- memory 470 may store a subset of the modules and data structures identified above. Furthermore, memory 470 may store additional modules and data structures not described above.
- FIG. 5A illustrates an exemplary user interface for a menu of applications on portable multifunction device 200 in accordance with some embodiments. Similar user interfaces may be implemented on device 400 .
- user interface 500 includes the following elements, or a subset or superset thereof:
- icon labels illustrated in FIG. 5A are merely exemplary.
- icon 522 for video and music player module 252 may optionally be labeled “Music” or “Music Player.”
- Other labels are, optionally, used for various application icons.
- a label for a respective application icon includes a name of an application corresponding to the respective application icon.
- a label for a particular application icon is distinct from a name of an application corresponding to the particular application icon.
- FIG. 5B illustrates an exemplary user interface on a device (e.g., device 400 , FIG. 4 ) with a touch-sensitive surface 551 (e.g., a tablet or touchpad 455 , FIG. 4 ) that is separate from the display 550 (e.g., touch screen display 212 ).
- Device 400 also, optionally, includes one or more contact intensity sensors (e.g., one or more of sensors 457 ) for detecting intensity of contacts on touch-sensitive surface 551 and/or one or more tactile output generators 459 for generating tactile outputs for a user of device 400 .
- one or more contact intensity sensors e.g., one or more of sensors 457
- tactile output generators 459 for generating tactile outputs for a user of device 400 .
- the device detects inputs on a touch-sensitive surface that is separate from the display, as shown in FIG. 5B .
- the touch-sensitive surface e.g., 551 in FIG. 5B
- the touch-sensitive surface has a primary axis (e.g., 552 in FIG. 5B ) that corresponds to a primary axis (e.g., 553 in FIG. 5B ) on the display (e.g., 550 ).
- the device detects contacts (e.g., 560 and 562 in FIG.
- finger inputs e.g., finger contacts, finger tap gestures, finger swipe gestures
- one or more of the finger inputs are replaced with input from another input device (e.g., a mouse-based input or stylus input).
- a swipe gesture is, optionally, replaced with a mouse click (e.g., instead of a contact) followed by movement of the cursor along the path of the swipe (e.g., instead of movement of the contact).
- a tap gesture is, optionally, replaced with a mouse click while the cursor is located over the location of the tap gesture (e.g., instead of detection of the contact followed by ceasing to detect the contact).
- multiple user inputs are simultaneously detected, it should be understood that multiple computer mice are, optionally, used simultaneously, or a mouse and finger contacts are, optionally, used simultaneously.
- FIG. 6A illustrates exemplary personal electronic device 600 .
- Device 600 includes body 602 .
- device 600 can include some or all of the features described with respect to devices 200 and 400 (e.g., FIGS. 2A-4B ).
- device 600 has touch-sensitive display screen 604 , hereafter touch screen 604 .
- touch screen 604 may have one or more intensity sensors for detecting intensity of contacts (e.g., touches) being applied.
- the one or more intensity sensors of touch screen 604 (or the touch-sensitive surface) can provide output data that represents the intensity of touches.
- the user interface of device 600 can respond to touches based on their intensity, meaning that touches of different intensities can invoke different user interface operations on device 600 .
- device 600 has one or more input mechanisms 606 and 608 .
- Input mechanisms 606 and 608 can be physical. Examples of physical input mechanisms include push buttons and rotatable mechanisms.
- device 600 has one or more attachment mechanisms. Such attachment mechanisms, if included, can permit attachment of device 600 with, for example, hats, eyewear, earrings, necklaces, shirts, jackets, bracelets, watch straps, chains, trousers, belts, shoes, purses, backpacks, and so forth. These attachment mechanisms may permit device 600 to be worn by a user.
- FIG. 6B depicts exemplary personal electronic device 600 .
- device 600 can include some or all of the components described with respect to FIGS. 2A, 2B , and 4 .
- Device 600 has bus 612 that operatively couples I/O section 614 with one or more computer processors 616 and memory 618 .
- I/O section 614 can be connected to display 604 , which can have touch-sensitive component 622 and, optionally, touch-intensity sensitive component 624 .
- I/O section 614 can be connected with communication unit 630 for receiving application and operating system data, using Wi-Fi, Bluetooth, near field communication (NFC), cellular, and/or other wireless communication techniques.
- Device 600 can include input mechanisms 606 and/or 608 .
- Input mechanism 606 may be a rotatable input device or a depressible and rotatable input device, for example.
- Input mechanism 608 may be a button, in some examples.
- Input mechanism 608 may be a microphone, in some examples.
- Personal electronic device 600 can include various sensors, such as GPS sensor 632 , accelerometer 634 , directional sensor 640 (e.g., compass), gyroscope 636 , motion sensor 638 , and/or a combination thereof, all of which can be operatively connected to I/O section 614 .
- sensors such as GPS sensor 632 , accelerometer 634 , directional sensor 640 (e.g., compass), gyroscope 636 , motion sensor 638 , and/or a combination thereof, all of which can be operatively connected to I/O section 614 .
- Memory 618 of personal electronic device 600 can be a non-transitory computer-readable storage medium, for storing computer-executable instructions, which, when executed by one or more computer processors 616 , for example, can cause the computer processors to perform the techniques described below, including process 900 ( FIGS. 8A-D ).
- the computer-executable instructions can also be stored and/or transported within any non-transitory computer-readable storage medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
- a “non-transitory computer-readable storage medium” can be any medium that can tangibly contain or store computer-executable instructions for use by or in connection with the instruction execution system, apparatus, or device.
- the non-transitory computer-readable storage medium can include, but is not limited to, magnetic, optical, and/or semiconductor storages. Examples of such storage include magnetic disks, optical discs based on CD, DVD, or Blu-ray technologies, as well as persistent solid-state memory such as flash, solid-state drives, and the like.
- Personal electronic device 600 is not limited to the components and configuration of FIG. 6B , but can include other or additional components in multiple configurations.
- the term “affordance” refers to a user-interactive graphical user interface object that may be displayed on the display screen of devices 200 , 400 , and/or 600 ( FIGS. 2, 4, and 6 ).
- an image e.g., icon
- a button e.g., button
- text e.g., hyperlink
- the term “focus selector” refers to an input element that indicates a current part of a user interface with which a user is interacting.
- the cursor acts as a “focus selector” so that when an input (e.g., a press input) is detected on a touch-sensitive surface (e.g., touchpad 455 in FIG. 4 or touch-sensitive surface 551 in FIG. 5B ) while the cursor is over a particular user interface element (e.g., a button, window, slider or other user interface element), the particular user interface element is adjusted in accordance with the detected input.
- a touch screen display e.g., touch-sensitive display system 212 in FIG.
- a detected contact on the touch screen acts as a “focus selector” so that when an input (e.g., a press input by the contact) is detected on the touch screen display at a location of a particular user interface element (e.g., a button, window, slider, or other user interface element), the particular user interface element is adjusted in accordance with the detected input.
- an input e.g., a press input by the contact
- a particular user interface element e.g., a button, window, slider, or other user interface element
- focus is moved from one region of a user interface to another region of the user interface without corresponding movement of a cursor or movement of a contact on a touch screen display (e.g., by using a tab key or arrow keys to move focus from one button to another button); in these implementations, the focus selector moves in accordance with movement of focus between different regions of the user interface.
- the focus selector is generally the user interface element (or contact on a touch screen display) that is controlled by the user so as to communicate the user's intended interaction with the user interface (e.g., by indicating, to the device, the element of the user interface with which the user is intending to interact).
- a focus selector e.g., a cursor, a contact, or a selection box
- a press input is detected on the touch-sensitive surface (e.g., a touchpad or touch screen) will indicate that the user is intending to activate the respective button (as opposed to other user interface elements shown on a display of the device).
- the term “characteristic intensity” of a contact refers to a characteristic of the contact based on one or more intensities of the contact. In some embodiments, the characteristic intensity is based on multiple intensity samples. The characteristic intensity is, optionally, based on a predefined number of intensity samples, or a set of intensity samples collected during a predetermined time period (e.g., 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10 seconds) relative to a predefined event (e.g., after detecting the contact, prior to detecting liftoff of the contact, before or after detecting a start of movement of the contact, prior to detecting an end of the contact, before or after detecting an increase in intensity of the contact, and/or before or after detecting a decrease in intensity of the contact).
- a predefined time period e.g., 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10 seconds
- a characteristic intensity of a contact is, optionally based on one or more of: a maximum value of the intensities of the contact, a mean value of the intensities of the contact, an average value of the intensities of the contact, a top 10 percentile value of the intensities of the contact, a value at the half maximum of the intensities of the contact, a value at the 90 percent maximum of the intensities of the contact, or the like.
- the duration of the contact is used in determining the characteristic intensity (e.g., when the characteristic intensity is an average of the intensity of the contact over time).
- the characteristic intensity is compared to a set of one or more intensity thresholds to determine whether an operation has been performed by a user.
- the set of one or more intensity thresholds may include a first intensity threshold and a second intensity threshold.
- a contact with a characteristic intensity that does not exceed the first threshold results in a first operation
- a contact with a characteristic intensity that exceeds the first intensity threshold and does not exceed the second intensity threshold results in a second operation
- a contact with a characteristic intensity that exceeds the second threshold results in a third operation.
- a comparison between the characteristic intensity and one or more thresholds is used to determine whether or not to perform one or more operations (e.g., whether to perform a respective operation or forgo performing the respective operation) rather than being used to determine whether to perform a first operation or a second operation.
- a portion of a gesture is identified for purposes of determining a characteristic intensity.
- a touch-sensitive surface may receive a continuous swipe contact transitioning from a start location and reaching an end location, at which point the intensity of the contact increases.
- the characteristic intensity of the contact at the end location may be based on only a portion of the continuous swipe contact, and not the entire swipe contact (e.g., only the portion of the swipe contact at the end location).
- a smoothing algorithm may be applied to the intensities of the swipe contact prior to determining the characteristic intensity of the contact.
- the smoothing algorithm optionally includes one or more of: an unweighted sliding-average smoothing algorithm, a triangular smoothing algorithm, a median filter smoothing algorithm, and/or an exponential smoothing algorithm.
- these smoothing algorithms eliminate narrow spikes or dips in the intensities of the swipe contact for purposes of determining a characteristic intensity.
- the intensity of a contact on the touch-sensitive surface may be characterized relative to one or more intensity thresholds, such as a contact-detection intensity threshold, a light press intensity threshold, a deep press intensity threshold, and/or one or more other intensity thresholds.
- the light press intensity threshold corresponds to an intensity at which the device will perform operations typically associated with clicking a button of a physical mouse or a trackpad.
- the deep press intensity threshold corresponds to an intensity at which the device will perform operations that are different from operations typically associated with clicking a button of a physical mouse or a trackpad.
- the device when a contact is detected with a characteristic intensity below the light press intensity threshold (e.g., and above a nominal contact-detection intensity threshold below which the contact is no longer detected), the device will move a focus selector in accordance with movement of the contact on the touch-sensitive surface without performing an operation associated with the light press intensity threshold or the deep press intensity threshold.
- a characteristic intensity below the light press intensity threshold e.g., and above a nominal contact-detection intensity threshold below which the contact is no longer detected
- these intensity thresholds are consistent between different sets of user interface figures.
- An increase of characteristic intensity of the contact from an intensity below the light press intensity threshold to an intensity between the light press intensity threshold and the deep press intensity threshold is sometimes referred to as a “light press” input.
- An increase of characteristic intensity of the contact from an intensity below the deep press intensity threshold to an intensity above the deep press intensity threshold is sometimes referred to as a “deep press” input.
- An increase of characteristic intensity of the contact from an intensity below the contact-detection intensity threshold to an intensity between the contact-detection intensity threshold and the light press intensity threshold is sometimes referred to as detecting the contact on the touch-surface.
- a decrease of characteristic intensity of the contact from an intensity above the contact-detection intensity threshold to an intensity below the contact-detection intensity threshold is sometimes referred to as detecting liftoff of the contact from the touch-surface.
- the contact-detection intensity threshold is zero. In some embodiments, the contact-detection intensity threshold is greater than zero.
- one or more operations are performed in response to detecting a gesture that includes a respective press input or in response to detecting the respective press input performed with a respective contact (or a plurality of contacts), where the respective press input is detected based at least in part on detecting an increase in intensity of the contact (or plurality of contacts) above a press-input intensity threshold.
- the respective operation is performed in response to detecting the increase in intensity of the respective contact above the press-input intensity threshold (e.g., a “down stroke” of the respective press input).
- the press input includes an increase in intensity of the respective contact above the press-input intensity threshold and a subsequent decrease in intensity of the contact below the press-input intensity threshold, and the respective operation is performed in response to detecting the subsequent decrease in intensity of the respective contact below the press-input threshold (e.g., an “up stroke” of the respective press input).
- the device employs intensity hysteresis to avoid accidental inputs sometimes termed “jitter,” where the device defines or selects a hysteresis intensity threshold with a predefined relationship to the press-input intensity threshold (e.g., the hysteresis intensity threshold is X intensity units lower than the press-input intensity threshold or the hysteresis intensity threshold is 75%, 90%, or some reasonable proportion of the press-input intensity threshold).
- the hysteresis intensity threshold is X intensity units lower than the press-input intensity threshold or the hysteresis intensity threshold is 75%, 90%, or some reasonable proportion of the press-input intensity threshold.
- the press input includes an increase in intensity of the respective contact above the press-input intensity threshold and a subsequent decrease in intensity of the contact below the hysteresis intensity threshold that corresponds to the press-input intensity threshold, and the respective operation is performed in response to detecting the subsequent decrease in intensity of the respective contact below the hysteresis intensity threshold (e.g., an “up stroke” of the respective press input).
- the press input is detected only when the device detects an increase in intensity of the contact from an intensity at or below the hysteresis intensity threshold to an intensity at or above the press-input intensity threshold and, optionally, a subsequent decrease in intensity of the contact to an intensity at or below the hysteresis intensity, and the respective operation is performed in response to detecting the press input (e.g., the increase in intensity of the contact or the decrease in intensity of the contact, depending on the circumstances).
- the descriptions of operations performed in response to a press input associated with a press-input intensity threshold or in response to a gesture including the press input are, optionally, triggered in response to detecting either: an increase in intensity of a contact above the press-input intensity threshold, an increase in intensity of a contact from an intensity below the hysteresis intensity threshold to an intensity above the press-input intensity threshold, a decrease in intensity of the contact below the press-input intensity threshold, and/or a decrease in intensity of the contact below the hysteresis intensity threshold corresponding to the press-input intensity threshold.
- the operation is, optionally, performed in response to detecting a decrease in intensity of the contact below a hysteresis intensity threshold corresponding to, and lower than, the press-input intensity threshold.
- FIG. 7A illustrates a block diagram of digital assistant system 700 in accordance with various examples.
- digital assistant system 700 can be implemented on a standalone computer system.
- digital assistant system 700 can be distributed across multiple computers.
- some of the modules and functions of the digital assistant can be divided into a server portion and a client portion, where the client portion resides on one or more user devices (e.g., devices 104 , 122 , 200 , 400 , or 600 ) and communicates with the server portion (e.g., server system 108 ) through one or more networks, e.g., as shown in FIG. 1 .
- digital assistant system 700 can be an implementation of server system 108 (and/or DA server 106 ) shown in FIG.
- digital assistant system 700 is only one example of a digital assistant system, and that digital assistant system 700 can have more or fewer components than shown, may combine two or more components, or may have a different configuration or arrangement of the components.
- the various components shown in FIG. 7A can be implemented in hardware, software instructions for execution by one or more processors, firmware, including one or more signal processing and/or application specific integrated circuits, or a combination thereof.
- Digital assistant system 700 can include memory 702 , one or more processors 704 , input/output (I/O) interface 706 , and network communications interface 708 . These components can communicate with one another over one or more communication buses or signal lines 710 .
- memory 702 can include a non-transitory computer-readable medium, such as high-speed random access memory and/or a non-volatile computer-readable storage medium (e.g., one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices).
- a non-transitory computer-readable medium such as high-speed random access memory and/or a non-volatile computer-readable storage medium (e.g., one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices).
- I/O interface 706 can couple input/output devices 716 of digital assistant system 700 , such as displays, keyboards, touch screens, and microphones, to user interface module 722 .
- I/O interface 706 in conjunction with user interface module 722 , can receive user inputs (e.g., voice input, keyboard inputs, touch inputs, etc.) and processes them accordingly.
- digital assistant system 700 can include any of the components and I/O communication interfaces described with respect to devices 200 , 400 , or 600 in FIGS. 2A, 4, 6A -B, respectively.
- digital assistant system 700 can represent the server portion of a digital assistant implementation, and can interact with the user through a client-side portion residing on a user device (e.g., devices 104 , 200 , 400 , or 600 ).
- the network communications interface 708 can include wired communication port(s) 712 and/or wireless transmission and reception circuitry 714 .
- the wired communication port(s) can receive and send communication signals via one or more wired interfaces, e.g., Ethernet, Universal Serial Bus (USB), FIREWIRE, etc.
- the wireless circuitry 714 can receive and send RF signals and/or optical signals from/to communications networks and other communications devices.
- the wireless communications can use any of a plurality of communications standards, protocols, and technologies, such as GSM, EDGE, CDMA, TDMA, Bluetooth, Wi-Fi, VoIP, Wi-MAX, or any other suitable communication protocol.
- Network communications interface 708 can enable communication between digital assistant system 700 with networks, such as the Internet, an intranet, and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN), and/or a metropolitan area network (MAN), and other devices.
- networks such as the Internet, an intranet, and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN), and/or a metropolitan area network (MAN), and other devices.
- networks such as the Internet, an intranet, and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN), and/or a metropolitan area network (MAN), and other devices.
- networks such as the Internet, an intranet, and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN), and/or a metropolitan area network (MAN), and other devices.
- LAN wireless local area network
- MAN metropolitan area network
- memory 702 can store programs, modules, instructions, and data structures including all or a subset of: operating system 718 , communications module 720 , user interface module 722 , one or more applications 724 , and digital assistant module 726 .
- memory 702 or the computer-readable storage media of memory 702 , can store instructions for performing process 900 , described below.
- processors 704 can execute these programs, modules, and instructions, and reads/writes from/to the data structures.
- Operating system 718 can include various software components and/or drivers for controlling and managing general system tasks (e.g., memory management, storage device control, power management, etc.) and facilitates communications between various hardware, firmware, and software components.
- general system tasks e.g., memory management, storage device control, power management, etc.
- Communications module 720 can facilitate communications between digital assistant system 700 with other devices over network communications interface 708 .
- communications module 720 can communicate with RF circuitry 208 of electronic devices such as devices 200 , 400 , and 600 shown in FIG. 2A, 4, 6A -B, respectively.
- Communications module 720 can also include various components for handling data received by wireless circuitry 714 and/or wired communications port 712 .
- User interface module 722 can receive commands and/or inputs from a user via I/O interface 706 (e.g., from a keyboard, touch screen, pointing device, controller, and/or microphone), and generate user interface objects on a display. User interface module 722 can also prepare and deliver outputs (e.g., speech, sound, animation, text, icons, vibrations, haptic feedback, light, etc.) to the user via the I/O interface 706 (e.g., through displays, audio channels, speakers, touch-pads, etc.).
- outputs e.g., speech, sound, animation, text, icons, vibrations, haptic feedback, light, etc.
- Applications 724 can include programs and/or modules that are configured to be executed by one or more processors 704 .
- applications 724 can include user applications, such as games, a calendar application, a navigation application, or an email application.
- applications 724 can include resource management applications, diagnostic applications, or scheduling applications, for example.
- Memory 702 can also store digital assistant module 726 (or the server portion of a digital assistant).
- digital assistant module 726 can include the following sub-modules, or a subset or superset thereof: input/output processing module 728 , speech-to-text (STT) processing module 730 , natural language processing module 732 , dialogue flow processing module 734 , task flow processing module 736 , service processing module 738 , and speech synthesis module 740 .
- STT speech-to-text
- Each of these modules can have access to one or more of the following systems or data and models of the digital assistant module 726 , or a subset or superset thereof: ontology 760 , vocabulary index 744 , user data 748 , task flow models 754 , service models 756 , and ASR systems.
- the digital assistant can perform at least some of the following: converting speech input into text; identifying a user's intent expressed in a natural language input received from the user; actively eliciting and obtaining information needed to fully infer the user's intent (e.g., by disambiguating words, games, intentions, etc.); determining the task flow for fulfilling the inferred intent; and executing the task flow to fulfill the inferred intent.
- I/O processing module 728 can interact with the user through I/O devices 716 in FIG. 7A or with a user device (e.g., devices 104 , 200 , 400 , or 600 ) through network communications interface 708 in FIG. 7A to obtain user input (e.g., a speech input) and to provide responses (e.g., as speech outputs) to the user input.
- I/O processing module 728 can optionally obtain contextual information associated with the user input from the user device, along with or shortly after the receipt of the user input.
- the contextual information can include user-specific data, vocabulary, and/or preferences relevant to the user input.
- the contextual information also includes software and hardware states of the user device at the time the user request is received, and/or information related to the surrounding environment of the user at the time that the user request was received.
- I/O processing module 728 can also send follow-up questions to, and receive answers from, the user regarding the user request. When a user request is received by I/O processing module 728 and the user request can include speech input, I/O processing module 728 can forward the speech input to STT processing module 730 (or speech recognizer) for speech-to-text conversions.
- STT processing module 730 can include one or more ASR systems.
- the one or more ASR systems can process the speech input that is received through I/O processing module 728 to produce a recognition result.
- Each ASR system can include a front-end speech pre-processor.
- the front-end speech pre-processor can extract representative features from the speech input.
- the front-end speech pre-processor can perform a Fourier transform on the speech input to extract spectral features that characterize the speech input as a sequence of representative multi-dimensional vectors.
- each ASR system can include one or more speech recognition models (e.g., acoustic models and/or language models) and can implement one or more speech recognition engines.
- Examples of speech recognition models can include Hidden Markov Models, Gaussian-Mixture Models, Deep Neural Network Models, n-gram language models, and other statistical models.
- Examples of speech recognition engines can include the dynamic time warping based engines and weighted finite-state transducers (WFST) based engines.
- the one or more speech recognition models and the one or more speech recognition engines can be used to process the extracted representative features of the front-end speech pre-processor to produce intermediate recognitions results (e.g., phonemes, phonemic strings, and sub-words), and ultimately, text recognition results (e.g., words, word strings, or sequence of tokens).
- the speech input can be processed at least partially by a third-party service or on the user's device (e.g., device 104 , 200 , 400 , or 600 ) to produce the recognition result.
- STT processing module 730 produces recognition results containing a text string (e.g., words, or sequence of words, or sequence of tokens)
- the recognition result can be passed to natural language processing module 732 for intent deduction.
- STT processing module 730 can include and/or access a vocabulary of recognizable words via phonetic alphabet conversion module 731 .
- Each vocabulary word can be associated with one or more candidate pronunciations of the word represented in a speech recognition phonetic alphabet.
- the vocabulary of recognizable words can include a word that is associated with a plurality of candidate pronunciations.
- the vocabulary may include the word “tomato” that is associated with the candidate pronunciations of / / and / /.
- vocabulary words can be associated with custom candidate pronunciations that are based on previous speech inputs from the user.
- Such custom candidate pronunciations can be stored in STT processing module 730 and can be associated with a particular user via the user's profile on the device.
- the candidate pronunciations for words can be determined based on the spelling of the word and one or more linguistic and/or phonetic rules.
- the candidate pronunciations can be manually generated, e.g., based on known canonical pronunciations.
- the candidate pronunciations can be ranked based on the commonness of the candidate pronunciation. For example, the candidate pronunciation / / can be ranked higher than / /, because the former is a more commonly used pronunciation (e.g., among all users, for users in a particular geographical region, or for any other appropriate subset of users).
- candidate pronunciations can be ranked based on whether the candidate pronunciation is a custom candidate pronunciation associated with the user. For example, custom candidate pronunciations can be ranked higher than canonical candidate pronunciations. This can be useful for recognizing proper nouns having a unique pronunciation that deviates from canonical pronunciation.
- candidate pronunciations can be associated with one or more speech characteristics, such as geographic origin, nationality, or ethnicity.
- the candidate pronunciation / / can be associated with the United States, whereas the candidate pronunciation / / can be associated with Great Britain.
- the rank of the candidate pronunciation can be based on one or more characteristics (e.g., geographic origin, nationality, ethnicity, etc.) of the user stored in the user's profile on the device. For example, it can be determined from the user's profile that the user is associated with the United States. Based on the user being associated with the United States, the candidate pronunciation / / (associated with the United States) can be ranked higher than the candidate pronunciation / / (associated with Great Britain). In some examples, one of the ranked candidate pronunciations can be selected as a predicted pronunciation (e.g., the most likely pronunciation).
- STT processing module 730 can be used to determine the phonemes corresponding to the speech input (e.g., using an acoustic model), and then attempt to determine words that match the phonemes (e.g., using a language model). For example, if STT processing module 730 can first identify the sequence of phonemes / / corresponding to a portion of the speech input, it can then determine, based on vocabulary index 744 , that this sequence corresponds to the word “tomato.”
- STT processing module 730 can use approximate matching techniques to determine words in an utterance. Thus, for example, the STT processing module 730 can determine that the sequence of phonemes / / corresponds to the word “tomato,” even if that particular sequence of phonemes is not one of the candidate sequence of phonemes for that word.
- natural language processing module 732 can be configured to receive metadata associated with the speech input.
- the metadata can indicate whether to perform natural language processing on the speech input (or the sequence of words or tokens corresponding to the speech input). If the metadata indicates that natural language processing is to be performed, then the natural language processing module can receive the sequence of words or tokens from the STT processing module to perform natural language processing. However, if the metadata indicates that natural language process is not to be performed, then the natural language processing module can be disabled and the sequence of words or tokens (e.g., text string) from the STT processing module can be outputted from the digital assistant.
- the metadata can further identify one or more domains corresponding to the user request.
- the natural language processor can disable domains in ontology 760 other than the one or more domains. In this way, natural language processing is constrained to the one or more domains in ontology 760 .
- the structure query (described below) can be generated using the one or more domains and not the other domains in the ontology.
- Natural language processing module 732 (“natural language processor”) of the digital assistant can take the sequence of words or tokens (“token sequence”) generated by STT processing module 730 , and attempt to associate the token sequence with one or more “actionable intents” recognized by the digital assistant.
- An “actionable intent” can represent a task that can be performed by the digital assistant, and can have an associated task flow implemented in task flow models 754 .
- the associated task flow can be a series of programmed actions and steps that the digital assistant takes in order to perform the task.
- the scope of a digital assistant's capabilities can be dependent on the number and variety of task flows that have been implemented and stored in task flow models 754 , or in other words, on the number and variety of “actionable intents” that the digital assistant recognizes.
- the effectiveness of the digital assistant can also be dependent on the assistant's ability to infer the correct “actionable intent(s)” from the user request expressed in natural language.
- natural language processing module 732 can also receive contextual information associated with the user request, e.g., from I/O processing module 728 .
- the natural language processing module 732 can optionally use the contextual information to clarify, supplement, and/or further define the information contained in the token sequence received from STT processing module 730 .
- the contextual information can include, for example, user preferences, hardware, and/or software states of the user device, sensor information collected before, during, or shortly after the user request, prior interactions (e.g., dialogue) between the digital assistant and the user, and the like.
- contextual information can be dynamic, and can change with time, location, content of the dialogue, and other factors.
- the natural language processing can be based on, e.g., ontology 760 .
- Ontology 760 can be a hierarchical structure containing many nodes, each node representing either an “actionable intent” or a “property” relevant to one or more of the “actionable intents” or other “properties.”
- an “actionable intent” can represent a task that the digital assistant is capable of performing, i.e., it is “actionable” or can be acted on.
- a “property” can represent a parameter associated with an actionable intent or a sub-aspect of another property.
- a linkage between an actionable intent node and a property node in ontology 760 can define how a parameter represented by the property node pertains to the task represented by the actionable intent node.
- ontology 760 can be made up of actionable intent nodes and property nodes.
- each actionable intent node can be linked to one or more property nodes either directly or through one or more intermediate property nodes.
- each property node can be linked to one or more actionable intent nodes either directly or through one or more intermediate property nodes.
- ontology 760 can include a “restaurant reservation” node (i.e., an actionable intent node).
- Property nodes “restaurant,” “date/time” (for the reservation), and “party size” can each be directly linked to the actionable intent node (i.e., the “restaurant reservation” node).
- property nodes “cuisine,” “price range,” “phone number,” and “location” can be sub-nodes of the property node “restaurant,” and can each be linked to the “restaurant reservation” node (i.e., the actionable intent node) through the intermediate property node “restaurant.”
- ontology 760 can also include a “set reminder” node (i.e., another actionable intent node).
- Property nodes “date/time” (for setting the reminder) and “subject” (for the reminder) can each be linked to the “set reminder” node.
- the property node “date/time” can be linked to both the “restaurant reservation” node and the “set reminder” node in ontology 760 .
- An actionable intent node along with its linked concept nodes, can be described as a “domain.”
- each domain can be associated with a respective actionable intent, and refers to the group of nodes (and the relationships there between) associated with the particular actionable intent.
- ontology 760 shown in FIG. 7C can include an example of restaurant reservation domain 762 and an example of reminder domain 764 within ontology 760 .
- the restaurant reservation domain includes the actionable intent node “restaurant reservation,” property nodes “restaurant,” “date/time,” and “party size,” and sub-property nodes “cuisine,” “price range,” “phone number,” and “location.”
- Reminder domain 764 can include the actionable intent node “set reminder,” and property nodes “subject” and “date/time.”
- ontology 760 can be made up of many domains. Each domain can share one or more property nodes with one or more other domains.
- the “date/time” property node can be associated with many different domains (e.g., a scheduling domain, a travel reservation domain, a movie ticket domain, etc.), in addition to restaurant reservation domain 762 and reminder domain 764 .
- FIG. 7C illustrates two example domains within ontology 760
- other domains can include, for example, “find a movie,” “initiate a phone call,” “find directions,” “schedule a meeting,” “send a message,” and “provide an answer to a question,” “read a list,” “providing navigation instructions,” “provide instructions for a task” and so on.
- a “send a message” domain can be associated with a “send a message” actionable intent node, and may further include property nodes such as “recipient(s),” “message type,” and “message body.”
- the property node “recipient” can be further defined, for example, by the sub-property nodes such as “recipient name” and “message address.”
- ontology 760 can include all the domains (and hence actionable intents) that the digital assistant is capable of understanding and acting upon.
- ontology 760 can be modified, such as by adding or removing entire domains or nodes, or by modifying relationships between the nodes within the ontology 760 .
- nodes associated with multiple related actionable intents can be clustered under a “super domain” in ontology 760 .
- a “travel” super-domain can include a cluster of property nodes and actionable intent nodes related to travel.
- the actionable intent nodes related to travel can include “airline reservation,” “hotel reservation,” “car rental,” “get directions,” “find points of interest,” and so on.
- the actionable intent nodes under the same super domain (e.g., the “travel” super domain) can have many property nodes in common.
- the actionable intent nodes for “airline reservation,” “hotel reservation,” “car rental,” “get directions,” and “find points of interest” can share one or more of the property nodes “start location,” “destination,” “departure date/time,” “arrival date/time,” and “party size.”
- each node in ontology 760 can be associated with a set of words and/or phrases that are relevant to the property or actionable intent represented by the node.
- the respective set of words and/or phrases associated with each node can be the so-called “vocabulary” associated with the node.
- the respective set of words and/or phrases associated with each node can be stored in vocabulary index 744 in association with the property or actionable intent represented by the node. For example, returning to FIG. 7B , the vocabulary associated with the node for the property of “restaurant” can include words such as “food,” “drinks,” “cuisine,” “hungry,” “eat,” “pizza,” “fast food,” “meal,” and so on.
- the vocabulary associated with the node for the actionable intent of “initiate a phone call” can include words and phrases such as “call,” “phone,” “dial,” “ring,” “call this number,” “make a call to,” and so on.
- the vocabulary index 744 can optionally include words and phrases in different languages.
- Natural language processing module 732 can receive the token sequence (e.g., a text string) from STT processing module 730 , and determine what nodes are implicated by the words in the token sequence. In some examples, if a word or phrase in the token sequence is found to be associated with one or more nodes in ontology 760 (via vocabulary index 744 ), the word or phrase can “trigger” or “activate” those nodes. Based on the quantity and/or relative importance of the activated nodes, natural language processing module 732 can select one of the actionable intents as the task that the user intended the digital assistant to perform. In some examples, the domain that has the most “triggered” nodes can be selected.
- the token sequence e.g., a text string
- the domain having the highest confidence value (e.g., based on the relative importance of its various triggered nodes) can be selected. In some examples, the domain can be selected based on a combination of the number and the importance of the triggered nodes. In some examples, additional factors are considered in selecting the node as well, such as whether the digital assistant has previously correctly interpreted a similar request from a user.
- User data 748 can include user-specific information, such as user-specific vocabulary, user preferences, user address, user's default and secondary languages, user's contact list, and other short-term or long-term information for each user.
- natural language processing module 732 can use the user-specific information to supplement the information contained in the user input to further define the user intent. For example, for a user request “invite my friends to my birthday party,” natural language processing module 732 can be able to access user data 748 to determine who the “friends” are and when and where the “birthday party” would be held, rather than requiring the user to provide such information explicitly in his/her request.
- natural language processing module 732 can generate a structured query to represent the identified actionable intent.
- the structured query can include parameters for one or more nodes within the domain for the actionable intent, and at least some of the parameters are populated with the specific information and requirements specified in the user request. For example, the user may say “Make me a dinner reservation at a sushi place at 7 .” In this case, natural language processing module 732 can be able to correctly identify the actionable intent to be “restaurant reservation” based on the user input.
- a structured query for a “restaurant reservation” domain may include parameters such as ⁇ Cuisine ⁇ , ⁇ Time ⁇ , ⁇ Date ⁇ , ⁇ Party Size ⁇ , and the like.
- the user's utterance contains insufficient information to complete the structured query associated with the domain.
- natural language processing module 732 can populate some parameters of the structured query with received contextual information. For example, in some examples, if the user requested a sushi restaurant “near me,” natural language processing module 732 can populate a ⁇ location ⁇ parameter in the structured query with GPS coordinates from the user device.
- natural language processing module 732 can pass the generated structured query (including any completed parameters) to task flow processing module 736 (“task flow processor”).
- Task flow processing module 736 can be configured to receive the structured query from natural language processing module 732 , complete the structured query, if necessary, and perform the actions required to “complete” the user's ultimate request.
- the various procedures necessary to complete these tasks can be provided in task flow models 754 .
- task flow models 754 can include procedures for obtaining additional information from the user and task flows for performing actions associated with the actionable intent.
- task flow processing module 736 may need to initiate additional dialogue with the user in order to obtain additional information, and/or disambiguate potentially ambiguous utterances.
- task flow processing module 736 can invoke dialogue flow processing module 734 to engage in a dialogue with the user.
- dialogue flow processing module 734 can determine how (and/or when) to ask the user for the additional information and receives and processes the user responses. The questions can be provided to and answers can be received from the users through I/O processing module 728 .
- dialogue flow processing module 734 can present dialogue output to the user via audio and/or visual output, and receives input from the user via spoken or physical (e.g., clicking) responses.
- dialogue flow processing module 734 when task flow processing module 736 invokes dialogue flow processing module 734 to determine the “party size” and “date” information for the structured query associated with the domain “restaurant reservation,” dialogue flow processing module 734 can generate questions such as “For how many people?” and “On which day?” to pass to the user. Once answers are received from the user, dialogue flow processing module 734 can then populate the structured query with the missing information, or pass the information to task flow processing module 736 to complete the missing information from the structured query.
- task flow processing module 736 can proceed to perform the ultimate task associated with the actionable intent. Accordingly, task flow processing module 736 can execute the steps and instructions in the task flow model according to the specific parameters contained in the structured query.
- the task flow model for the actionable intent of “restaurant reservation” can include steps and instructions for contacting a restaurant and actually requesting a reservation for a particular party size at a particular time.
- task flow processing module 736 can perform the steps of: (1) logging onto a server of the ABC Café or a restaurant reservation system such as OPENTABLE®, (2) entering the date, time, and party size information in a form on the website, (3) submitting the form, and (4) making a calendar entry for the reservation in the user's calendar.
- task flow processing module 736 can perform the steps of: (1) logging onto a server of the ABC Café or a restaurant reservation system such as OPENTABLE®, (2) entering the date, time, and party size information in a form on the website, (3) submitting the form, and (4) making a calendar entry for the reservation in the user's calendar.
- task flow processing module 736 can employ the assistance of service processing module 738 (“service processing module”) to complete a task requested in the user input or to provide an informational answer requested in the user input.
- service processing module 738 can act on behalf of task flow processing module 736 to make a phone call, set a calendar entry, invoke a map search, invoke or interact with other user applications installed on the user device, and invoke or interact with third-party services (e.g., a restaurant reservation portal, a social networking website, a banking portal, etc.).
- the protocols and application programming interfaces (API) required by each service can be specified by a respective service model among service models 756 .
- Service processing module 738 can access the appropriate service model for a service and generate requests for the service in accordance with the protocols and APIs required by the service according to the service model.
- service processing module 738 can establish a network connection with the online reservation service using the web address stored in the service model, and send the necessary parameters of the reservation (e.g., time, date, party size) to the online reservation interface in a format according to the API of the online reservation service.
- natural language processing module 732 , dialogue flow processing module 734 , and task flow processing module 736 can be used collectively and iteratively to infer and define the user's intent, obtain information to further clarify and refine the user intent, and finally generate a response (i.e., an output to the user, or the completion of a task) to fulfill the user's intent.
- the generated response can be a dialogue response to the speech input that at least partially fulfills the user's intent. Further, in some examples, the generated response can be output as a speech output.
- the generated response can be sent to speech synthesis module 740 (e.g., speech synthesizer) where it can be processed to synthesize the dialogue response in speech form.
- the generated response can be data content relevant to satisfying a user request in the speech input.
- Speech synthesis module 740 can be configured to synthesize speech outputs for presentation to the user. Speech synthesis module 740 synthesizes speech outputs based on text provided by the digital assistant. For example, the generated dialogue response can be in the form of a text string. Speech synthesis module 740 can convert the text string to an audible speech output. Speech synthesis module 740 can use any appropriate speech synthesis technique in order to generate speech outputs from text, including, but not limited, to concatenative synthesis, unit selection synthesis, diphone synthesis, domain-specific synthesis, formant synthesis, articulatory synthesis, hidden Markov model (HMM) based synthesis, and sinewave synthesis.
- HMM hidden Markov model
- speech synthesis module 740 can be configured to synthesize individual words based on phonemic strings corresponding to the words. For example, a phonemic string can be associated with a word in the generated dialogue response. The phonemic string can be stored in metadata associated with the word. Speech synthesis model 740 can be configured to directly process the phonemic string in the metadata to synthesize the word in speech form.
- speech synthesis can be performed on a remote device (e.g., the server system 108 ), and the synthesized speech can be sent to the user device for output to the user. For example, this can occur in some implementations where outputs for a digital assistant are generated at a server system. And because server systems generally have more processing power or resources than a user device, it can be possible to obtain higher quality speech outputs than would be practical with client-side synthesis.
- FIGS. 8A-8Q illustrate exemplary user interfaces for discovering media based on a nonspecific, unstructured natural language request, in accordance with some embodiments.
- the user interfaces in these figures are used to illustrate the processes described below, including the exemplary processes in FIGS. 9A-9C .
- an electronic device 200 includes a display 212 and a microphone 213 in accordance with some embodiments.
- a digital assistant, as described above is, accessed by a user, who utters unstructured natural language user input that is acquired via the microphone 213 .
- the timing of the user request is under the control of the user.
- the user can request the delivery of media during the concurrent playback of other media by the electronic device 200 , or while the electronic device 200 is not playing back media.
- the user input requests the delivery of particular media, in this case a song.
- the user input is converted from speech to text, and in accordance with some embodiments, the textual user input 1000 is displayed on the display 212 .
- the user can verify that the digital assistant has received correctly the request as made.
- the textual user input 1000 is not displayed.
- the user has requested the digital assistant to play a specific track from an album entitled “Liszt: The Piano Concertos.”
- At least part of the album is stored in electronic form on the electronic device 200 , in some embodiments.
- at least part of the album is stored remotely (in the “cloud”) on an external device accessible to the electronic device 200 .
- the remotely stored content is associated with the electronic device 200 and/or a unique identifier associated with the user, in accordance with some embodiments.
- at least part of the album is part of a streaming service, such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.), that is accessible to the electronic device 200 .
- the digital assistant Upon receiving unstructured natural language user input requesting media, the digital assistant causes a search for that media to be performed, as described in greater detail with regard to FIGS. 9A-9C . That search is performed utilizing the unstructured natural language user input, and the context of that input. In this example, the search finds the specific media requested by the user, track 2 of “Liszt: The Piano Concertos,” determining based on the user input and its context that the specific album satisfies the user request. In some embodiments, it is transparent to the user whether the media requested by the user is locally present on the electronic device 200 , stored remotely on a server, or streamed to the user by a streaming service such as Apple Music or iTunes RadioTM (services of Apple, Inc.
- a streaming service such as Apple Music or iTunes RadioTM (services of Apple, Inc.
- the digital assistant obtains the requested media.
- the electronic device 200 presents an identifier 1002 associated with the media on the display 212 , in accordance with some embodiments, to allow the user to confirm which media is being played back.
- the electronic device 200 includes a media playback interface 1004 which includes standard media controls, such as affordances for pausing, reversing, or advancing media, affordances for controlling volume, and an affordance that displays and/or controls progress in media playback, in accordance with some embodiments.
- the electronic device 200 plays back the selected media; here, track 2 (“Piano Concerto #2 in A) from the album “Liszt: The Piano Concertos.”
- Nonspecific unstructured natural language user input does not identify a particular media item with particularity. For example, a user wishes to hear a song associated with a popular movie, but does not know or recall the name of the song.
- User input 1010 is received, which identifies the movie but not the song: “play that song from Top Gun.”
- the user request made in FIG. 8C may be made at any time: during, after, before, or instead of playback of the media obtained as shown in FIG. 8B .
- the user input 1010 is displayed on the display 212 , in accordance with some embodiments.
- the digital assistant Upon receiving nonspecific unstructured natural language user input requesting media, the digital assistant causes a search for that media to be performed, as described in greater detail with regard to FIGS. 9A-9C . That search is performed utilizing the unstructured natural language user input, and the context of that input.
- the context of the user input may include one or more of device context, user context, and social context.
- Device context includes information associated with the electronic device 200 itself.
- the device context includes the location of the electronic device 200 .
- a GPS system or other system may be used to localize the electronic device 200 , and may be able to determine whether the user is moving, where the user is located (e.g., home, school, work, park, gym), and other information.
- the electronic device 200 is configured to receive signals from a wireless location transmitter other than GPS, such as a Bluetooth® wireless location transmitter, or an iBeacon of Apple, Inc., Cupertino, Calif.
- the digital assistant determines that the electronic device 200 , and thus the user, is moving at a rate of speed consistent with automobile travel.
- the digital assistant utilizes this information in conjunction with user context (described below) that is related to the media most often played back by the user in the car in order to obtain requested media, in accordance with some embodiments.
- the digital assistant determines that the electronic device 200 is at a venue in which live music is performed, such as an arena or a bar.
- the digital assistant may cause a search for a schedule of musical performances at the location where the electronic device 200 is located, and utilize that information to satisfy the user request for media, in accordance with some embodiments.
- the digital assistant determines that the user is at home watching television.
- the device context includes audio input from the microphone other than user speech, such as sound in the vicinity of the electronic device 200 .
- the electronic device generates an acoustic fingerprint from that sound.
- An acoustic fingerprint is a condensed digital summary, generated from that sound, that can be used to identify that sound by comparing that acoustic fingerprint to a database.
- the electronic device in other embodiments, also or instead converts that sound to text, where that sound includes recognizable speech.
- the digital assistant determines based on the sound in the vicinity of the electronic device 200 that the user is watching a particular television program, such as through the Apple TV® digital media extender of Apple, Inc., Cupertino, Calif.
- the digital assistant also utilizes a database of television programming schedule information to make such a determination, in accordance with some embodiments.
- the digital assistant Upon receiving a request from a user for media (e.g., “record episodes of this show”; “get this song from the show”), the digital assistant utilizes location and ambient sound information to determine which media satisfies a user request.
- the user is walking through a mall or public space, or sitting in a restaurant, and hears a song over the local sound system.
- the digital assistant may listen to ambient sound via the microphone 213 in order to determine what the user meant by “this song.”
- the digital assistant may add that song to a user library.
- the device context includes the content of media concurrently played by the electronic device 200 at the same time as the user request for media.
- Such media can be in any format, such as audio and/or video.
- the video and music player module 252 accesses information associated with the media concurrently played by the electronic device 200 , in some embodiments, such that the digital assistant 200 has direct access to that information.
- Such information is useful in contexts where the user requests media that is related to the media concurrently played by the electronic device (e.g., “play more like this,” “I want to hear the live version of this song”).
- the device context includes a timecode associated with the content of media concurrently played by the electronic device 200 at the same time as the user request for media.
- the digital assistant utilizes this timecode, in accordance with some embodiments, to determine the location in the media that is concurrent with the user request for media. For example, if a user is watching a video on the electronic device, and requests “add this artist to my stream,” the digital assistant accesses the media stream played by the video and music player module 252 to determine which media is being played concurrently, then uses the timecode of that media stream to determine if a song is associated with that timecode in the media stream; if so, the digital assistant determines that song is associated with the user input of “this artist,” and determines the artist who performed that song. Similarly, in accordance with some embodiments, the electronic device 200 receives streaming audio from a source such as Apple Music or iTunes RadioTM (services of Apple, Inc.
- a source such as Apple Music or iTunes RadioTM (services of Apple, Inc.
- the digital assistant determines which song is playing, such as by inspecting metadata associated with the streaming audio, by generating an acoustic fingerprint from the streaming audio and comparing that acoustic fingerprint to a database (as described above), or by querying the server from which the streaming audio is received. The digital assistant then presents the song title and artist to the user, using text and/or audio.
- the device context includes data associated with media stored on the electronic device 200 .
- the digital assistant infers that media stored on the electronic device 200 is media that is preferred by a user, and utilizes that information in determining the meaning of nonspecific user requests for media.
- the data associated with media stored on the electronic device includes, for example, but is not limited to the presence of that media, bibliographic information of that media (e.g., title, album, release date), information relating to the playback history of that media (e.g., number of times the media has been played back; date the media was last played back; date the media was added to the electronic device), and metadata relating to that media.
- the device context includes the application context.
- Application context is related to the application the user is utilizing for media playback.
- the digital assistant determines whether concurrent media playback is being performed by the video and music player module 252 , by a native application running on the electronic device 200 , by a third-party application associated with the electronic device 200 (e.g., HuluPlus® of Hulu, LLC, Santa Monica, Calif.), or by another application.
- the application context also includes metadata, if any, associated with the application.
- User context includes information associated with the user of the electronic device 200 .
- User context includes the content of natural language user input requesting media.
- user context includes demographic information about the user, such as the user's age, gender, or the like.
- the digital assistant uses this information to compare the request for media to similar requests made by other users with similar demographic profiles, in some embodiments. For example, a digital assistant receives nonspecific unstructured natural language user input requesting media from a user who attends college in Boston. The digital assistant causes a search to be made relating to media sought by other college students in Boston, and uses the popularity of media among similarly-situated users in order to obtain media for the user.
- the user context includes media associated with the user, regardless of the storage location of the media.
- Such media may be stored in the cloud, or may be associated with a streaming music service accessible to the user, such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.).
- the digital assistant infers that media associated with the user is media that is preferred by a user, and utilizes that information in determining the meaning of nonspecific user requests for media.
- user context further includes data associated with the media associated with the user, such as but not limited to the presence of that media, bibliographic information of that media (e.g., title, album, release date), information relating to the playback history of that media (e.g., number of times the media has been played back; date the media was last played back; date the media was added to the electronic device), and metadata relating to that media.
- bibliographic information of that media e.g., title, album, release date
- information relating to the playback history of that media e.g., number of times the media has been played back; date the media was last played back; date the media was added to the electronic device
- metadata relating to that media.
- the user context includes information relating to the musical preferences of the user.
- the user context includes the history of media played back by the user, and/or the number of times the user has played back certain items, regardless of the storage location of those items. Media that has been played more often by the user is inferred to be preferred by the user, such that media that has been played frequently by the user that matches nonspecific natural language user input requesting media is considered a better match when determining a media item that satisfies a user request.
- the user context includes the history of media acquisition by the user, regardless of the storage location of that media.
- the user context includes the history of the addition of music to a streaming music service accessible to the user, such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.).
- the user context includes data associated with user content accessible by the electronic device 200 .
- user context includes data associated with digital photographs taken by the user, whether stored on the electronic device 200 , or stored remotely to and accessible by the electronic device 200 .
- Digital photographs typically are stored along with metadata such as the date taken and the location taken.
- the digital assistant may cause a search to be performed for information relating to a trip to Italy.
- the digital assistant determines the corresponding date information in that photograph metadata.
- the digital assistant then causes a search to be made of databases of historical music chart information (e.g., the database of Billboard of New York, N.Y.) based on the date information obtained from the photograph.
- databases of historical music chart information e.g., the database of Billboard of New York, N.Y.
- the user content need not be related to the type of media sought by the user.
- Social context includes information associated with other users than the user of the electronic device 200 .
- social context includes how many times a particular media item has been streamed or downloaded from a music service such as iTunes® music service of Apple, Inc. of Cupertino, Calif. Such a count of streams or downloads is performed across an artist's musical output, in one example. Such a count is performed within an album, in another example.
- the digital assistant may receive nonspecific natural language user input requesting media such as “play that song from Frozen.” The digital assistant may cause a search to be performed on the iTunes® music service of Apple, Inc.
- social context includes how many times a particular media item has been streamed from a streaming music service accessible to the user, such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.).
- social context includes the number of references to a media item in a social media database.
- the digital assistant may receive nonspecific natural language user input requesting media such as “I want to hear that big hit from Famous Band.” Famous Band may have released a popular album with several hits.
- the digital assistant may cause a search to be performed of a social database, e.g., the database of Twitter, Inc. of San Francisco, Calif., in order to determine how many mentions of a particular media item have been made across a recent period of time, such as the previous 7 days or 14 days.
- the particular media item from Famous Band with the most references in that period of time is obtained by the digital assistant.
- user input 1010 has been received, which identifies a movie but not the requested song from the movie: “play that song from Top Gun.”
- the digital assistant identifies at least one context of the user input 1010 , as described above.
- the context is at least one of device context, user context and social context.
- the digital assistant causes a search for the media, based on the context and on the user input. For example, the digital assistant may search the electronic device 200 and/or media associated with the user for the soundtrack for the movie “Top Gun.” Upon discovering the soundtrack, the digital assistant may determine which song on the soundtrack has been played the most, and determine that song satisfies the media request, after which the digital assistant obtains the song for the user.
- the digital assistant may search a music service for the soundtrack for the movie “Top Gun.” Upon discovering the soundtrack, the digital assistant may determine which song on the soundtrack has been streamed or downloaded the most times, and determine that song satisfies the media request, after which the digital assistant obtains the song for the user.
- Both of these example processes may be performed simultaneously in order to obtain the requested media.
- the time to locate the media item is reduced, particularly where only one of several processes delivers a result that satisfies the user request.
- the parallel processes each deliver a single media item, confidence that it is the media item requested by the user is enhanced.
- the digital assistant applies further heuristics to those items to determine which is the most likely to meet the user request.
- the digital assistant may score each media item on one or more criteria, and determine that the media item with the highest score satisfies the user request, after which the digital assistant obtains the song for the user.
- the scoring methodology is biased toward certain results, such as results associated with media stored on the electronic device 200 , according to some embodiments.
- a user selects which criteria are more or less important with regard to scoring in order to obtain the requested media.
- the digital assistant obtains the requested media.
- the electronic device 200 presents an identifier 1012 associated with the media on the display 212 , in accordance with some embodiments, to allow the user to confirm which media is being played back: here, the song “Danger Zone” from Kenny Loggins, on the Top Gun Original Motion Picture Soundtrack Album.
- the electronic device 200 optionally includes a media playback interface 1004 as described above. The electronic device 200 plays back the selected media.
- the digital assistant receives user input 1020 requesting alternate media.
- the alternate media is a different song from the same movie (i.e., the same soundtrack album).
- the user input 1020 need not be phrased as a request; as shown in FIG.
- the user input 1020 states “No, I meant the other one.”
- the digital assistant performs speech-to-text conversion on the user input 1020 , and determines from the context of the most recent request and most recent digital assistant action that the user wishes to receive a different media item than the one most recently obtained.
- the digital assistant causes a search for the requested media based on the context, the user input, and the second user input. For example, the digital assistant may cause another search based on the same criteria as the first search, but where media items that match the first result (here, the song “Danger Zone”) are discarded as potential matches.
- the results of the previous search are still loaded in memory accessible to the digital assistant, and the digital assistant selects the next-highest match out of a list of possible matching media items.
- This approach may require more storage capacity but delivers faster results to the user.
- the digital assistant determines at least one additional media item that satisfies the request.
- the electronic device 200 plays streaming media, such as streaming audio from Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.). If the user wants to skip ahead to the next song, the user may request “skip this song,” “next song,” or the like.
- the digital assistant need not perform a search based on that request for media. Instead, according to some embodiments, the digital assistant transmits a signal to the server from which the streaming audio is received requesting that the stream skip ahead to the next song. In response, the digital assistant receives another song, which is then played by the electronic device 200 .
- the digital assistant obtains the media that satisfies the request.
- the electronic device 200 presents an identifier 1022 associated with the media on the display 212 , in accordance with some embodiments, to allow the user to confirm which media is being played back: here, the song “Take My Breath Away (Love Theme from Top Gun)” from Berlin, on the Top Gun Original Motion Picture Soundtrack Album.
- the electronic device 200 optionally includes a media playback interface 1004 as described above. The electronic device 200 plays back the selected media.
- the digital assistant receives user input 1030 requesting alternate media.
- the alternate media is a different version of the song.
- the different version is a live version rather than a studio version.
- the different version is a different studio version by the same artist, a different live version by the same artist, or the same song recorded by a different artist.
- the digital assistant causes a search for alternate media and determines at least one alternate media item that satisfies the request, in the same manner as described above with regard to FIGS. 8E-8F .
- the digital assistant obtains the media that satisfies the request.
- the electronic device 200 presents an identifier 1032 associated with the media on the display 212 , in accordance with some embodiments, to allow the user to confirm which media is being played back: here, the song “Take My Breath Away Live” from Berlin, on the album entitled “Live: Sacred and Profane.”
- the electronic device 200 optionally includes a media playback interface 1004 as described above. The electronic device 200 plays back the selected media.
- the digital assistant receives user input requesting media associated with a specific date in the past.
- the digital assistant Upon receiving nonspecific natural language user input requesting media such as “play popular music from my birthday,” the digital assistant causes a search to be performed for user context information relating to the user's birthday.
- the user's birthday is stored on the electronic device 200 , or is stored in association with a user account that in turn is associated with the electronic device 200 and/or a service or program that transmits media to the electronic device, such as the iTunes® application program, Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.).
- the digital assistant Upon determining the date of the user's birthday, the digital assistant then causes a search to be made of one or more databases of historical music chart information (e.g., the database of Billboard of New York, N.Y.) based on the date of the user's birthday.
- the digital assistant receives historical music chart information from one or more databases, and in response obtains for the user (through the use of streaming audio or by downloading) and plays one or more of the songs identified by that historical music chart information.
- the user requests “play the top ten hits from 1978.”
- the digital assistant causes a search to be made of one or more databases of historical music chart information (e.g., the database of Billboard of New York, N.Y.) based on the specified date of 1978.
- the digital assistant receives historical music chart information from the one or more databases, and in response obtains for the user (through the use of streaming audio or by downloading) and plays the top ten songs of 1978, as identified by that historical music chart information.
- the digital assistant causes the songs to be played in countdown order, from the #10 hit “Three Times a Lady” by the Commodores, to #1 hit “Shadow Dancing” by Andy Gibb. Alternately, the digital assistant causes the songs to be played from #1 to #10, or plays the top ten songs in random order.
- the digital assistant receives nonspecific user input requesting media associated with a particular artist. For example, the user requests “play the latest album from Famous Band.”
- the digital assistant causes a search to be made of one or more databases of music information (such as the iTunes® music service, or Apple Music, of Apple, Inc. of Cupertino, Calif.) based on the specified artist Famous Band.
- the digital assistant receives discography information from the one or more databases, including the name of the most recent album of Famous Band, and in response obtains for the user (through the use of streaming audio or by downloading) and plays the latest album from Famous Band.
- a streaming media service such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.)
- the digital assistant initially queries the streaming media service for the latest album by the specified artist Famous Band, and in response receives an audio stream of the latest album by Famous Band.
- the digital assistant receives input from a user associated with user satisfaction with the media.
- the electronic device 200 receives speech or text input corresponding to a user liking the media (i.e., a “like”).
- a “like” input from the user is user context information.
- the “like” input may be utilized as part of the social context with regard to other users. For example, if a user “likes” a particular media item, it may be inferred that others of similar demographic characteristics, and/or in a similar location, will be more interested in that particular media item.
- the user's “like” of a particular media item is stored locally on the electronic device 200 , is stored on the cloud in association with the user, or is part of a streaming music service accessible to the user, such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.).
- a streaming music service accessible to the user, such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.).
- the electronic device 200 receives speech or text input corresponding to a user disliking the media (i.e., a “dislike”).
- a “dislike” input from the user is user context information.
- the “dislike” input may be utilized as part of the social context with regard to other users. For example, if a user “dislikes” a particular media item, it may be inferred that others of similar demographic characteristics, and/or in a similar location, will be less interested in that particular media item.
- the user's “dislike” of a particular media item is stored locally on the electronic device 200 , is stored on the cloud in association with the user, or is part of a streaming music service accessible to the user, such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.).
- the digital assistant upon receiving a “dislike” input, the digital assistant Upon receiving a “dislike” input, the digital assistant interrupts concurrent playback of media already playing on the electronic device 200 , skips ahead to the next media in a playback queue or media stream, ceases playing media, and/or takes other action, according to some embodiments.
- a user request to skip a particular media item counts as a partial or complete “dislike” of that media item. In other embodiments, a user request to skip a media item is not counted as a “dislike” of that media item.
- the digital assistant receives user input requesting new music. For example, the user requests “play new music.”
- the digital assistant identifies at least one context of the user input, as described above.
- the context is at least one of device context, user context and social context.
- the digital assistant transmits a request for new music to a streaming music service accessible to the user, such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.).
- the digital assistant receives an audio stream from the streaming music service, including one or more new songs (e.g., songs released in the past 14 days).
- selection of the one or more new songs in the audio is based at least in part on previous “like” and “dislike” inputs received from the user relative to other media, and/or other user context, device context, and/or social context.
- the user requests “play new country songs.”
- the digital assistant transmits a request for new music in the genre of country to a streaming music service accessible to the user, such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.).
- the digital assistant receives an audio stream from the streaming music service, including one or more new country songs.
- selection of the one or more new country songs in the audio is based at least in part on previous “like” and “dislike” inputs received from the user relative to other media, and/or other user context, device context, and/or social context.
- the digital assistant receives a user request to play additional similar media. For example, the user requests “play more like this.”
- the digital assistant identifies at least one context of the user input, as described above.
- the context is at least one of device context, user context and social context.
- the digital assistant determines which song is playing, such as by inspecting metadata associated with the currently-playing audio, by generating an acoustic fingerprint from the streaming audio and comparing that acoustic fingerprint to a database (as described above), by querying a server from which streaming audio is received, and/or any other suitable action or actions.
- the digital assistant causes a search for the media, based on the context and on the user input.
- the digital assistant may search the electronic device 200 and/or media associated with the user for similar media, such as based on genre, artist, and user context of media that the user has previously “liked” or “disliked.”
- the digital assistant then obtains (from the electronic device 200 , from a streaming music service, or other source) media for the user.
- the digital assistant may search a music service for similar music.
- the digital assistant causes a search to be made of one or more databases of music information (such as the iTunes® music service, or Apple Music, of Apple, Inc.
- the digital assistant receives information associated with songs from the one or more databases and in response obtains for the user (through the use of streaming audio or by downloading) and plays similar music.
- a streaming media service such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.)
- the digital assistant initially queries the streaming media service for similar media, and in response receives an audio stream of similar media responsive to the user request.
- the digital assistant When the digital assistant obtains media, the digital assistant interrupts concurrent playback of media already playing on the electronic device 200 , places the media in an ordered queue for later playback, adds the media to a media library, and/or takes other action, according to some embodiments.
- the digital assistant determines based on the user input 1020 that the returned media item did not satisfy the user request, in accordance with some embodiments.
- the alternate media 1022 when the alternate media 1022 is obtained, it interrupts the concurrent playback of the song “Danger Zone,” terminating the playback of “Danger Zone” and replacing it with the playback of alternate media 1022 , in accordance with some embodiments.
- the digital assistant when the digital assistant determines that the user input is consistent with input requesting an interruption of concurrently-played media, the digital assistant causes the electronic device 200 to cease playing that media and replace it with the playback of the most-recently requested media.
- the media may be different types of media. For example, while watching a movie on the electronic device 200 , a user may request playback of a song; the digital assistant will cause the electronic device 200 to cease playing the movie and replace it with the playback of the most-recently requested media—in this example, the song.
- the digital assistant when the digital assistant obtains media, the digital assistant places the media in an ordered queue for later playback. As illustrated in FIG. 8J , the digital assistant receives user input 1040 requesting to “play more from this band.” The digital assistant determines based on the user input 1040 that the user is satisfied with the media item previously obtained, because the user wishes to obtain more media from the same artist. Other criteria may be used to determine whether user input 1040 is consistent with user satisfaction with the media being played concurrently with the user input 1040 . Based on that user input 1040 , the digital assistant causes a search to be made based on the user input and the context of the user input, determines one or more additional media items satisfying the user request, and obtains those one or more media items. As illustrated in FIG.
- the media playing concurrent with the user input 1040 continues to play.
- the digital assistant causes the one or more additional media items to be placed in an ordered queue for playback.
- the first item in the ordered queue is then played.
- the items in the queue may be from the local library on the electronic device 200 , may be located external to the electronic device in the cloud, or may be part of a streaming music service accessible to the user, such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.).
- the digital assistant when the digital assistant determines that the user input is consistent with input reflecting user satisfaction with concurrently-playing media, the digital assistant causes the electronic device 200 to continue playing that media and place one or more additional media items in an ordered queue for playback.
- the media may be different types of media, as set forth above with regard to another embodiment.
- the digital assistant when the digital assistant obtains media, the digital assistant adds the media to a media library associated with the user.
- the media library is locally stored on the electronic device 200 , is stored on the cloud in association with the user, or is part of a streaming music service accessible to the user, such as Apple Music or iTunes RadioTM (services of Apple, Inc. of Cupertino, Calif.).
- the digital assistant receives user input 1050 requesting “what is that song from Frozen?”
- the digital assistant causes a search for the media based on the user input and at least one context of the user input, determines at least one media item that satisfies the request, and obtains the at least one media item.
- the digital assistant automatically adds the obtained at least one media item to a media library associated with the user.
- the digital assistant upon obtaining the at least one media item, but before adding the at least one media item to a library associated with the user, the digital assistant presents the user with an option to add the at least one media item to a library associated with the user.
- the user is presented with an identifier 1052 of the at least one media item obtained, along with a request 1054 on the display 212 , such as “Add to library?”
- the electronic device displays a first affordance 1056 associated with adding the at least one media item to a library associated with the user, and a second affordance 1058 associated with not adding the at least one media item to a library associated with the user, in accordance with some embodiments.
- the digital assistant adds the at least one media item to a library associated with the user.
- the digital assistant may receive user input that annotates a media item.
- the electronic device 200 is playing back media item 1060 , which in this example is track 14 of the album “1970s Greatest Hits.”
- the audio interface 1004 may be displayed on the display 212 concurrently with playback of media item 1060 .
- the user may wish to annotate the media item 1060 .
- the digital assistant receives user input 1062 of unstructured natural language speech including one or more words, such as “I like these lyrics” or “What does this mean?”.
- the user input 1062 is associated with the timecode within the media item 1060 at which time the user input 1062 was received, according to some embodiments.
- the user input 1062 is converted from speech to text, stored as voice data, or handled in any other suitable manner.
- the user input 1062 in some embodiments, is a note from the user to himself or herself, or is other information upon which the digital assistant does not act.
- the digital assistant causes a search to be performed based on the user input 1062 based on the context of the user input 1062 , according to some embodiments. In other embodiments, the digital assistant does not cause a search to be performed until receiving an express request from the user. In response to the search, the digital assistant provides the search result 1064 to the user on the display 212 .
- the user input 1062 related to the meaning of the lyrics of the media item 1060 at a particular timecode, and the digital assistant determined the meaning of the lyrics such as by reference to a lyrics database.
- FIGS. 9A-9C illustrate a process 900 for operating a digital assistant according to various examples. More specifically, process 900 can be implemented to perform media discovery based on nonspecific natural language user input using a digital assistant.
- the process 900 can be performed using one or more electronic devices implementing a digital assistant.
- the process 900 can be performed using a client-server system (e.g., system 100 ) implementing a digital assistant.
- the individual blocks of the process 900 may be distributed in any appropriate manner among one or more computers, systems, or electronic devices. For instances, in some examples, process 900 can be performed entirely on an electronic device (e.g., devices 104 , 200 , 400 , or 600 ).
- references in this document to any one particular electronic device ( 104 , 200 , 400 , or 600 ) shall be understood to encompass all of the electronic devices ( 104 , 200 , 400 , or 600 ) unless one or more of those electronic devices ( 104 , 200 , 400 or 600 ) is excluded by the plain meaning of the text.
- the electronic device ( 104 , 200 , 400 or 600 ) utilized in several examples is a smartphone.
- the process 900 is not limited to use with a smartphone; the process 900 may be implemented on any other suitable electronic device, such as a tablet, a desktop computer, a laptop, or a smart watch. Electronic devices with greater computing power and greater battery life may perform more of the blocks of the process 900 .
- the distribution of blocks of the process 900 need not be fixed, and may vary depending upon network connection bandwidth, network connection quality, server load, availability of computer power and battery power at the electronic device (e.g., 104 , 200 , 400 , 600 ), and/or other factors. Further, while the following discussion describes process 900 as being performed by a digital assistant system (e.g., system 100 and/or digital assistant system 700 ), it should be recognized that the process or any particular part of the process is not limited to performance by any particular device, combination of devices, or implementation. The description of the process is further illustrated and exemplified by FIGS. 8A-8Q , and the description above related to those figures.
- FIGS. 9A-9C are a flow diagram 900 illustrating a method for discovering media based on a nonspecific, unstructured natural language request using a digital assistant and an electronic device ( 104 , 200 , 400 , or 600 ) in accordance with some embodiments. Some operations in process 900 may be combined, the order of some operations may be changed, and some operations may be omitted. In particular, optional operations indicated with dashed-line shapes in FIGS. 9A-9C may be performed in any suitable order, if at all, and need not be performed in the order set forth in FIGS. 9A-9C .
- method 900 provides an intuitive way for discovering media based on a nonspecific, unstructured natural language request using a digital assistant.
- the method reduces the cognitive burden on a user for discovering media based on a nonspecific, unstructured natural language request using a digital assistant, thereby creating a more efficient human-machine interface.
- enabling a user to discovering media based on a nonspecific, unstructured natural language request using a digital assistant more accurately and more efficiently conserves power and increases the time between battery charges.
- the digital assistant receives ( 902 ) user input associated with a request for media, where the user input includes unstructured natural language speech including one or more words.
- the electronic device e.g., 104 , 200 , 400 , 600
- receives ( 902 ) user input associated with a request for media where the user input includes unstructured natural language speech including one or more words.
- the electronic device e.g., 104 , 200 , 400 , 600
- the user input may also be referred to as an audio input or audio stream.
- the stream of audio can be received as raw sound waves, as an audio file, or in the form of a representative audio signal (analog or digital).
- the audio stream can be received at a remote system, such as a server component of a digital assistant.
- the audio stream can include user speech, such as a spoken user request.
- the user input may include a spoken user request by an authorized user.
- the user input may be received from a user who is closely associated with the electronic device ( 104 , 200 , 400 , 600 ) (e.g., the owner or predominant user of the user device).
- the user input is received in textual form instead of as speech.
- the audio stream is converted from speech to text by ASR processing prior to, or during, analysis by the digital assistant. Such conversion may be performed as described above, such as in paragraphs [ 0175 ] et seq. of this document.
- the digital assistant identifies ( 904 ) at least one context associated with the user input.
- the context includes one or more of device context, user context, and social context. Examples of each context and its use in media discovery are also set forth above.
- the digital assistant After identifying at least one context associated with the user input, the digital assistant causes ( 906 ) a search for the requested media based on the at least one context and the user input.
- the search is performed by the digital assistant itself.
- the search is requested by the digital assistant from a separate entity that performs the search and returns the results to the digital assistant.
- the search is both performed by the digital assistant itself and requested by the digital assistant from a separate entity. By performing both searches in parallel, response time to the user request of ( 902 ) is reduced.
- the search of block 906 may be performed locally, on the electronic device (e.g., 104 , 200 , 400 , 600 ), in accordance with some embodiments. In accordance with other embodiments, the search of block 906 may be performed remotely to the electronic device (e.g., 104 , 200 , 400 , 600 ). A search performed remotely to the electronic device (e.g., 104 , 200 , 400 , 600 ) may be performed at a server that includes or possesses access to information relative to the search, such as a server of Shazam Entertainment Limited of London, United Kingdom for audio fingerprint information, a server of Billboard Magazine of New York, N.Y. for historical music information, and/or a server of the iTunes® music service of Apple, Inc.
- the search is both performed locally and remotely to the electronic device (e.g., 104 , 200 , 400 , 600 ). By performing multiple searches in parallel, response time to the user request of ( 902 ) is reduced.
- the digital assistant determines ( 908 ), based on the at least one context and the user input, at least one media item that satisfies the request.
- the digital assistant makes this determination in any suitable manner.
- the digital assistant selects the first match that exceeds a predetermined threshold.
- the digital assistant determines ( 910 ) a probability, based on the at least one context and the user input, that at least one media item satisfies the request.
- the digital assistant determines ( 912 ) whether the probability exceeds a threshold.
- the threshold may be predetermined.
- the threshold may be user-adjustable.
- the threshold may be dynamically variable.
- the process 900 proceeds to the next block 918 .
- the digital assistant selects the best match of several candidate matches.
- the digital assistant determines ( 914 ) a probability, based on the at least one context and the user input, that at least one media item satisfies the request.
- the digital assistant selects the media item having the highest probability, and proceeds to the next block 918 . Examples of the determination 908 , based on the at least one context and the user input, of at least one media item that satisfies the request of block 902 , are also provided above relative to FIGS. 8A-8Q .
- the digital assistant obtains ( 918 ) the at least one media item.
- the digital assistant can obtain the at least one media item in several ways.
- the digital assistant automatically adds ( 920 ) the obtained at least one media item to a media library associated with the user, as described above with regard to FIGS. 8A-8Q .
- the digital assistant presents ( 922 ) the user with an option to add the obtained media to a media library associated with the user, and in response to user selection of the option to add the obtained media to a media library associated with the user, adds ( 924 ) the obtained media to a media library associated with the user.
- the digital assistant places ( 926 ) the obtained media in an ordered queue, and then plays ( 928 ) the media according to the queue.
- the digital assistant may determine ( 930 ) whether a local library includes the at least one media item.
- the local library is located on the electronic device (e.g., 104 , 200 , 400 , 600 ).
- the digital assistant By searching the local library first, or in parallel with causing an external search, the amount of time required to satisfy the user request is reduced when the requested item is located on the electronic device (e.g., 104 , 200 , 400 , 600 ). If the digital assistant determines that the local library includes the at least one media item, the digital assistant presents ( 932 ) the at least one media item to the user. If the digital assistant determines that the local library does not include the at least one media item, the digital assistant obtains ( 934 ) the at least one media item from an external data source.
- the digital assistant plays ( 936 ) the media item. In some circumstances, where the digital assistant determines that the user wishes to interrupt the concurrent playback of other media, the digital assistant terminates ( 938 ) the concurrent playback of other media, as described above with regard to FIGS. 8A-8Q .
- the digital assistant receives ( 940 ) a second user input including unstructured natural language speech including one or more words.
- the digital assistant annotates ( 942 ) the media item with the one or more words.
- the process stops here, if the user desires simply to make and retain a note in association with the media item.
- the process continues, and the digital assistant causes ( 944 ) a search to be performed based on the annotation.
- the digital assistant presents ( 946 ) the search result to the user. This process is described above, with particular reference to FIGS. 8N-8Q and the accompanying text in the specification.
- the digital assistant receives ( 948 ) a second user input requesting user material.
- this may occur when the digital assistant originally obtained a media item that did not match the user's request. This situation is described above, with particular reference to FIGS. 8E-8F and the accompanying text in the specification. As another example, this may occur when the digital assistant originally obtained a media item that matched a user's request, but user wishes to hear different media. This situation is described above, with particular reference to FIGS. 8G-8H and the accompanying text in the specification.
- the digital assistant causes ( 950 ) a search for the media based on the at least one context, the user input, and the second user input.
- the combination of the user input and the second user input provides additional search criteria that are useful in determining the media item.
- the combination of the user input and the second user input allows the digital assistant to exclude the original result when evaluating search results.
- the digital assistant determines ( 952 ), based on the at least one context, the user input and the second user input, at least one additional media item that satisfies the request. In accordance with a determination that the at least one additional media item satisfies the request, the digital assistant obtains ( 954 ) the at least one additional media item. Further, in accordance with some embodiments, the probability that a media item satisfies the request for media can be updated over time, based on, for example, the at least one context, the user input, and the second user input requesting user material.
- FIG. 10 shows an exemplary functional block diagram of an electronic device 1000 configured in accordance with the principles of the various described embodiments.
- the functional blocks of electronic device 1000 are configured to perform the techniques described above.
- the functional blocks of the device 1000 are, optionally, implemented by hardware, software, or a combination of hardware and software to carry out the principles of the various described examples. It is understood by persons of skill in the art that the functional blocks described in FIG. 10 are, optionally, combined or separated into sub-blocks to implement the principles of the various described examples. Therefore, the description herein optionally supports any possible combination or separation or further definition of the functional blocks described herein.
- an electronic device 1000 includes a display unit 1002 configured to display a graphic user interface, optionally, a touch-sensitive surface unit 1004 configured to receive contacts, a microphone unit 1006 configured to receive audio signals, and a processing unit 1008 coupled to the display unit 1002 and, optionally, the touch-sensitive surface unit 1004 and microphone unit 1006 .
- the processing unit 1008 includes a receiving unit 1010 , an identifying unit 1012 , a causing unit 1014 , a determining unit 1016 , an obtaining unit 1018 , and a playing unit 1020 .
- the processing unit is configured to receive (e.g., with receiving unit 1010 ) user input associated with a request for media, the user input comprising unstructured natural language speech including one or more words; identify (e.g., with identifying unit 1012 ) at least one context associated with the user input; cause (e.g., with causing unit 1014 ) a search for the media based on the at least one context and the user input; determine (e.g., with determining unit 1016 ) based on the at least one context and the user input, at least one media item that satisfies the request; and in accordance with a determination that the at least one media item satisfies the request, obtain (e.g., with obtaining unit 1018 ) the at least one media item.
- receive e.g., with receiving unit 1010
- user input comprising unstructured natural language speech including one or more words
- identify e.g., with identifying unit 1012
- cause e.g., with causing unit 1014
- the causing unit is further configured to cause (e.g., with causing unit 1014 ) searching to be performed locally on the device.
- the causing unit is further configured to cause (e.g., with causing unit 1014 ) searching to be performed remotely to the device.
- the processing unit is further configured to determine (e.g., with determining unit 1016 ) whether a local library includes the media item; and in accordance with a determination that the local library includes the media item, present (e.g., with playing unit 1020 ) the media item to the user; in accordance with a determination that the local library does not include the media item, obtain (e.g., with obtaining unit 1018 ) the media item from an external data source.
- the processing unit is further configured to receive (e.g., with receiving unit 1010 ) second user input requesting alternate media; in response to receiving the second user input, cause (e.g., with causing unit 1014 ) a search for the media based on the at least one context, the user input and the second user input; determine (e.g., with determining unit 1016 ) based on the at least one context, the user input and the second user input, at least one additional media item that satisfies the request; and in accordance with a determination that the at least one additional media item satisfies the request, obtain (e.g., with obtaining unit 1018 ) the at least one additional media item.
- the at least one context associated with the user input includes a device context.
- the device context includes the location of the device.
- the device context includes the proximity of the device to a wireless location transmitter.
- the device context includes the content of media concurrently played by the device.
- the device context includes a timecode associated with media concurrently played by the device.
- the device context includes audio input from the microphone other than user speech.
- the device context includes data associated with media stored on the device.
- the device context includes application context.
- the at least one context associated with the user input includes a user context.
- the user context includes the content of the user input.
- the user context includes media associated with the user.
- the user context includes demographic information about the user.
- the user context includes information relating to the musical preferences of the user.
- the user context includes data associated with user content accessible by the device.
- the at least one context associated with the user input includes a social context.
- the social context includes the access frequency of a particular media item across a plurality of users.
- the social context includes the number of references to a media item in a social media database.
- the media item is a song.
- the processing unit is further configured to, in response to obtaining the at least one media item, play (e.g., with playing unit 1020 ) at least one media item, and terminate (e.g., with playing unit 1020 ) concurrent playback of other media.
- the processing unit is further configured to, in response to obtaining the media item, place (e.g., with playing unit 1020 ) the at least one obtained media item in an ordered queue; and play (e.g., with playing unit 1020 ) the at least one media item according to the queue.
- the obtaining unit is further configured to add the at least one media item to a media library associated with the user.
- the processing unit is further configured to present (e.g., with the display unit 1002 ) the user with an option to add the at least one media item to a media library associated with the user; and in response to user selection of the option to add the at least one media item to a media library associated with the user, add (e.g., with the obtaining unit 1018 ) the at least one media item to a media library associated with the user.
- the processing unit is further configured to, after obtaining the media item, receive (e.g., with the receiving unit 1010 ) second user input comprising unstructured natural language speech including one or more words; and annotate (e.g. with the processing unit 1008 ) the media item with the one or more words.
- the processing unit is further configured to cause (e.g., with the causing unit 1014 ) a search to be performed based on the annotation; and present (e.g., with the display unit 1002 ) the search result to the user.
- the determining unit is further configured to determine (e.g., with the determining unit 1016 ) a probability, based on the at least one context and the user input, that at least one media item satisfies the request; and determine (e.g., with the determining unit 1016 ) whether the probability exceeds a threshold.
- the determining unit is further configured to determine (e.g., with the determining unit 1016 ) a probability, based on the at least one context and the user input, that at least one media item satisfies the request; and selecting (e.g., with the determining unit 1016 ) the media item having the highest probability.
- the receiving unit is further configured to receive streaming audio containing the at least one media item.
- FIGS. 9A-9C are, optionally, implemented by components depicted in FIGS. 1A-7C or FIG. 10 . It would be clear to a person having ordinary skill in the art how processes can be implemented based on the components depicted in FIGS. 1A-7C or FIG. 10 .
- this gathered data may include personal information data that uniquely identifies or can be used to contact or locate a specific person.
- personal information data can include demographic data, location-based data, telephone numbers, email addresses, home addresses, or any other identifying information.
- the present disclosure recognizes that the use of such personal information data, in the present technology, can be used to the benefit of users.
- the personal information data can be used to deliver targeted content that is of greater interest to the user. Accordingly, use of such personal information data enables calculated control of the delivered content. Further, other uses for personal information data that benefit the user are also contemplated by the present disclosure.
- the present disclosure further contemplates that the entities responsible for the collection, analysis, disclosure, transfer, storage, or other use of such personal information data will comply with well-established privacy policies and/or privacy practices.
- such entities should implement and consistently use privacy policies and practices that are generally recognized as meeting or exceeding industry or governmental requirements for maintaining personal information data private and secure.
- personal information from users should be collected for legitimate and reasonable uses of the entity and not shared or sold outside of those legitimate uses. Further, such collection should occur only after receiving the informed consent of the users.
- such entities would take any needed steps for safeguarding and securing access to such personal information data and ensuring that others with access to the personal information data adhere to their privacy policies and procedures. Further, such entities can subject themselves to evaluation by third parties to certify their adherence to widely accepted privacy policies and practices.
- the present disclosure also contemplates embodiments in which users selectively block the use of, or access to, personal information data. That is, the present disclosure contemplates that hardware and/or software elements can be provided to prevent or block access to such personal information data.
- the present technology can be configured to allow users to select to “opt in” or “opt out” of participation in the collection of personal information data during registration for services.
- users can select not to provide location information for targeted content delivery services.
- users can select to not provide precise location information, but permit the transfer of location zone information.
- the present disclosure broadly covers use of personal information data to implement one or more various disclosed embodiments, the present disclosure also contemplates that the various embodiments can also be implemented without the need for accessing such personal information data. That is, the various embodiments of the present technology are not rendered inoperable due to the lack of all or a portion of such personal information data.
- content can be selected and delivered to users by inferring preferences based on non-personal information data or a bare minimum amount of personal information, such as the content being requested by the device associated with a user, other non-personal information available to the content delivery services, or publically available information.
Abstract
Description
- This application claims priority to U.S. Provisional Patent Application No. 62/186,182, entitled “Virtual Assistant for Media Playback,” filed Jun. 29, 2015, the content of which is hereby incorporated by reference in its entirety for all purposes.
- The present disclosure relates generally to media playback, and more specifically to a virtual assistant used to facilitate media playback.
- Intelligent automated assistants (or digital assistants) provide a beneficial interface between human users and electronic devices. Such assistants allow users to interact with devices or systems using natural language in spoken and/or text forms. For example, a user can access the services of an electronic device by providing a spoken user request to a digital assistant associated with the electronic device. The digital assistant can interpret the user's intent from the spoken user request and operationalize the user's intent into tasks. The tasks can then be performed by executing one or more services of the electronic device and a relevant output can be returned to the user in natural language form.
- When managing music or other media, a digital assistant can be helpful in playing back specific media, particularly in a hands-free environment. A digital assistant can respond effectively to a request to play a specific media item, such as an album or a song identified specifically by title or by artist. However, digital assistants have not been useful in discovering media based on nonspecific, unstructured natural language requests—for example, a request for a song from a popular movie.
- Some techniques for discovering media based on a nonspecific, unstructured natural language request, however, are generally cumbersome and inefficient. For example, existing techniques use a complex and time-consuming user interface, which may include multiple key presses or keystrokes. The user must perform his or her own research to determine which specific media he or she is seeking, then attempt to obtain that media. Both of those steps may be impractical or impossible in certain circumstances, such as when the user is operating a motor vehicle or has his or her hands full. Existing techniques require more time than necessary, wasting user time and device energy. This latter consideration is particularly important in battery-operated devices.
- Accordingly, there is a need for electronic devices with faster, more efficient methods and interfaces for discovering media based on a nonspecific, unstructured natural language request. Such methods and interfaces optionally complement or replace other methods for discovering media based on a nonspecific, unstructured natural language request. Such methods and interfaces reduce the cognitive burden on a user and produce a more efficient human-machine interface. For battery-operated computing devices, such methods and interfaces conserve power and increase the time between battery charges.
- In some embodiments, a method for identifying media includes: at a device with one or more processors, memory, and a microphone: receiving user input associated with a request for media, the user input including unstructured natural language speech including one or more words; identifying at least one context associated with the user input; causing a search for the media based on the at least one context and the user input; determining, based on the at least one context and the user input, at least one media item that satisfies the request; and, in accordance with a determination that the at least one media item satisfies the request, obtaining the at least one media item.
- In some embodiments, an electronic device includes: a display; a memory; a microphone; a processor coupled to the display, the memory, and the microphone; the processor configured to: receive user input associated with a request for media, the user input including unstructured natural language speech including one or more words; identify at least one context associated with the user input; cause a search for the media based on the at least one context and the user input; determine, based on the at least one context and the user input, at least one media item that satisfies the request; and, in accordance with a determination that the at least one media item satisfies the request, obtain the at least one media item.
- In some embodiments, a non-transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to: receive user input associated with a request for media, the user input including unstructured natural language speech including one or more words; identify at least one context associated with the user input; cause a search for the media based on the at least one context and the user input; determine, based on the at least one context and the user input, at least one media item that satisfies the request; and in accordance with a determination that the at least one media item satisfies the request, obtain the at least one media item.
- In some embodiments, a transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to: receive user input associated with a request for media, the user input including unstructured natural language speech including one or more words; identify at least one context associated with the user input; cause a search for the media based on the at least one context and the user input; determine, based on the at least one context and the user input, at least one media item that satisfies the request; and, in accordance with a determination that the at least one media item satisfies the request, obtain the at least one media item.
- In some embodiments, a system utilizes an electronic device with a display, where the system includes: means for receiving user input associated with a request for media, the user input including unstructured natural language speech including one or more words; means for identifying at least one context associated with the user input; means for causing a search for the media based on the at least one context and the user input; means for determining, based on the at least one context and the user input, at least one media item that satisfies the request; and, in accordance with a determination that the at least one media item satisfies the request, means for obtaining the at least one media item.
- In some embodiments, an electronic device includes: a processing unit that includes a receiving unit, an identifying unit, a causing unit, a determining unit, and an obtaining unit, the processing unit configured to: receive, using the receiving unit, user input associated with a request for media, the user input including unstructured natural language speech including one or more words; identify, using the identifying unit, at least one context associated with the user input; cause, using the causing unit, a search for the media based on the at least one context and the user input; determine, using the determining unit, based on the at least one context and the user input, at least one media item that satisfies the request; and, in accordance with a determination that the at least one media item satisfies the request, obtain, using the obtaining unit, the at least one media item.
- Executable instructions for performing these functions are, optionally, included in a non-transitory computer-readable storage medium or other computer program product configured for execution by one or more processors. Executable instructions for performing these functions are, optionally, included in a transitory computer-readable storage medium or other computer program product configured for execution by one or more processors.
- Thus, devices are provided with faster, more efficient methods and interfaces for discovering media based on a nonspecific, unstructured natural language request, thereby increasing the effectiveness, efficiency, and user satisfaction with such devices. Such methods and interfaces may complement or replace other methods for discovering media based on a nonspecific, unstructured natural language request.
- For a better understanding of the various described embodiments, reference should be made to the Description of Embodiments below, in conjunction with the following drawings in which like reference numerals refer to corresponding parts throughout the figures.
-
FIG. 1 is a block diagram illustrating a system and environment for implementing a digital assistant according to various examples. -
FIG. 2A is a block diagram illustrating a portable multifunction device implementing the client-side portion of a digital assistant according to various examples. -
FIG. 2B is a block diagram illustrating exemplary components for event handling according to various examples. -
FIG. 3 illustrates a portable multifunction device implementing the client-side portion of a digital assistant according to various examples. -
FIG. 4 is a block diagram of an exemplary multifunction device with a display and a touch-sensitive surface according to various examples. -
FIG. 5A illustrates an exemplary user interface for a menu of applications on a portable multifunction device according to various examples. -
FIG. 5B illustrates an exemplary user interface for a multifunction device with a touch-sensitive surface that is separate from the display according to various examples. -
FIG. 6A illustrates a personal electronic device according to various examples. -
FIG. 6B is a block diagram illustrating a personal electronic device according to various examples. -
FIG. 7A is a block diagram illustrating a digital assistant system or a server portion thereof according to various examples. -
FIG. 7B illustrates the functions of the digital assistant shown inFIG. 7A according to various examples. -
FIG. 7C illustrates a portion of an ontology according to various examples. -
FIGS. 8A-8Q illustrate exemplary user interfaces for a personal electronic device in accordance with some embodiments.FIG. 8I is intentionally omitted to avoid any confusion between the capital letter I and the numeral 1 (one), andFIG. 8O is intentionally omitted to avoid any confusion between the capital letter O and the numeral 0 (zero). -
FIGS. 9A-9C illustrate a process for operating a digital assistant for media playback, according to various examples. -
FIG. 10 illustrates a functional block diagram of an electronic device according to various examples. - The following description sets forth exemplary methods, parameters, and the like. It should be recognized, however, that such description is not intended as a limitation on the scope of the present disclosure but is instead provided as a description of exemplary embodiments.
- There is a need for electronic devices that provide efficient methods and interfaces for discovering media based on a nonspecific, unstructured natural language request. As described above, media discovery techniques are not as effective as they might be, such as with users with slow or unusual speech patterns. A digital assistant can reduce the cognitive burden on a user who discovers media based on a nonspecific, unstructured natural language request, thereby enhancing productivity. Further, such techniques can reduce processor and battery power otherwise wasted on redundant user inputs.
- Below,
FIGS. 1, 2A-2B, 3, 4, 5A-5B and 6A-6B provide a description of exemplary devices for performing the techniques for discovering media based on a nonspecific, unstructured natural language request.FIG. 6A-6B illustrate exemplary user interfaces for discovering media based on a nonspecific, unstructured natural language request.FIGS. 7A-7C are block diagrams illustrating a digital assistant system or a server portion thereof, and a portion of an ontology associated with the digital assistant system.FIGS. 8A-8B are flow diagrams illustrating methods of discovering media based on a nonspecific, unstructured natural language request in accordance with some embodiments. - Although the following description uses terms “first,” “second,” etc. to describe various elements, these elements should not be limited by the terms. These terms are only used to distinguish one element from another. For example, a first touch could be termed a second touch, and, similarly, a second touch could be termed a first touch, without departing from the scope of the various described embodiments. The first touch and the second touch are both touches, but they are not the same touch.
- The terminology used in the description of the various described embodiments herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used in the description of the various described embodiments and the appended claims, the singular forms “a”, “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “includes,” “including,” “comprises,” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
- The term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context. Similarly, the phrase “if it is determined” or “if [a stated condition or event] is detected” may be construed to mean “upon determining” or “in response to determining” or “upon detecting [the stated condition or event]” or “in response to detecting [the stated condition or event],” depending on the context.
- Embodiments of electronic devices, user interfaces for such devices, and associated processes for using such devices are described. In some embodiments, the device is a portable communications device, such as a mobile telephone, that also contains other functions, such as PDA and/or music player functions. Exemplary embodiments of portable multifunction devices include, without limitation, the iPhone®, iPod Touch®, and iPad® devices from Apple Inc. of Cupertino, Calif. Other portable electronic devices, such as laptops or tablet computers with touch-sensitive surfaces (e.g., touch screen displays and/or touchpads), are, optionally, used. It should also be understood that, in some embodiments, the device is not a portable communications device, but is a desktop computer with a touch-sensitive surface (e.g., a touch screen display and/or a touchpad).
- In the discussion that follows, an electronic device that includes a display and a touch-sensitive surface is described. It should be understood, however, that the electronic device optionally includes one or more other physical user-interface devices, such as a physical keyboard, a mouse, and/or a joystick.
- The device may support a variety of applications, such as one or more of the following: a drawing application, a presentation application, a word processing application, a website creation application, a disk authoring application, a spreadsheet application, a gaming application, a telephone application, a video conferencing application, an e-mail application, an instant messaging application, a workout support application, a photo management application, a digital camera application, a digital video camera application, a web browsing application, a digital music player application, and/or a digital video player application.
- The various applications that are executed on the device optionally use at least one common physical user-interface device, such as the touch-sensitive surface. One or more functions of the touch-sensitive surface as well as corresponding information displayed on the device are, optionally, adjusted and/or varied from one application to the next and/or within a respective application. In this way, a common physical architecture (such as the touch-sensitive surface) of the device optionally supports the variety of applications with user interfaces that are intuitive and transparent to the user.
-
FIG. 1 illustrates a block diagram ofsystem 100 according to various examples. In some examples,system 100 can implement a digital assistant. The terms “digital assistant,” “virtual assistant,” “intelligent automated assistant,” or “automatic digital assistant” can refer to any information processing system that interprets natural language input in spoken and/or textual form to infer user intent, and performs actions based on the inferred user intent. For example, to act on an inferred user intent, the system can perform one or more of the following: identifying a task flow with steps and parameters designed to accomplish the inferred user intent, inputting specific requirements from the inferred user intent into the task flow; executing the task flow by invoking programs, methods, services, APIs, or the like; and generating output responses to the user in an audible (e.g., speech) and/or visual form. - Specifically, a digital assistant can be capable of accepting a user request at least partially in the form of a natural language command, request, statement, narrative, and/or inquiry. Typically, the user request can seek either an informational answer or performance of a task by the digital assistant. A satisfactory response to the user request can be a provision of the requested informational answer, a performance of the requested task, or a combination of the two. For example, a user can ask the digital assistant a question, such as “Where am I right now?” Based on the user's current location, the digital assistant can answer, “You are in Central Park near the west gate.” The user can also request the performance of a task, for example, “Please invite my friends to my girlfriend's birthday party next week.” In response, the digital assistant can acknowledge the request by saying “Yes, right away,” and then send a suitable calendar invite on behalf of the user to each of the user's friends listed in the user's electronic address book. During performance of a requested task, the digital assistant can sometimes interact with the user in a continuous dialogue involving multiple exchanges of information over an extended period of time. There are numerous other ways of interacting with a digital assistant to request information or performance of various tasks. In addition to providing verbal responses and taking programmed actions, the digital assistant can also provide responses in other visual or audio forms, e.g., as text, alerts, music, videos, animations, etc.
- As shown in
FIG. 1 , in some examples, a digital assistant can be implemented according to a client-server model. The digital assistant can include client-side portion 102 (hereafter “DAclient 102”) executed onuser device 104 and server-side portion 106 (hereafter “DA server 106”) executed onserver system 108. DAclient 102 can communicate withDA server 106 through one ormore networks 110. DAclient 102 can provide client-side functionalities such as user-facing input and output processing and communication withDA server 106. DAserver 106 can provide server-side functionalities for any number of DAclients 102 each residing on arespective user device 104. - In some examples,
DA server 106 can include client-facing I/O interface 112, one ormore processing modules 114, data andmodels 116, and I/O interface toexternal services 118. The client-facing I/O interface 112 can facilitate the client-facing input and output processing forDA server 106. One ormore processing modules 114 can utilize data andmodels 116 to process speech input and determine the user's intent based on natural language input. Further, one ormore processing modules 114 perform task execution based on inferred user intent. In some examples,DA server 106 can communicate withexternal services 120 through network(s) 110 for task completion or information acquisition. I/O interface toexternal services 118 can facilitate such communications. -
User device 104 can be any suitable electronic device. For example, user devices can be a portable multifunctional device (e.g.,device 200, described below with reference toFIG. 2A ), a multifunctional device (e.g.,device 400, described below with reference toFIG. 4 ), or a personal electronic device (e.g.,device 600, described below with reference toFIG. 6A-B .) A portable multifunctional device can be, for example, a mobile telephone that also contains other functions, such as PDA and/or music player functions. Specific examples of portable multifunction devices can include the iPhone®, iPod Touch®, and iPad® devices from Apple Inc. of Cupertino, Calif. Other examples of portable multifunction devices can include, without limitation, laptop or tablet computers. Further, in some examples,user device 104 can be a non-portable multifunctional device. In particular,user device 104 can be a desktop computer, a game console, a television, or a television set-top box. In some examples,user device 104 can include a touch-sensitive surface (e.g., touch screen displays and/or touchpads). Further,user device 104 can optionally include one or more other physical user-interface devices, such as a physical keyboard, a mouse, and/or a joystick. Various examples of electronic devices, such as multifunctional devices, are described below in greater detail. - Examples of communication network(s) 110 can include local area networks (LAN) and wide area networks (WAN), e.g., the Internet. Communication network(s) 110 can be implemented using any known network protocol, including various wired or wireless protocols, such as, for example, Ethernet, Universal Serial Bus (USB), FIREWIRE, Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Wi-Fi, voice over Internet Protocol (VoIP), Wi-MAX, or any other suitable communication protocol.
-
Server system 108 can be implemented on one or more standalone data processing apparatus or a distributed network of computers. In some examples,server system 108 can also employ various virtual devices and/or services of third-party service providers (e.g., third-party cloud service providers) to provide the underlying computing resources and/or infrastructure resources ofserver system 108. - In some examples,
user device 104 can communicate withDA server 106 viasecond user device 122.Second user device 122 can be similar or identical touser device 104. For example,second user device 122 can be similar todevices FIGS. 2A, 4, and 6A -B. User device 104 can be configured to communicatively couple tosecond user device 122 via a direct communication connection, such as Bluetooth, NFC, BTLE, or the like, or via a wired or wireless network, such as a local Wi-Fi network. In some examples,second user device 122 can be configured to act as a proxy betweenuser device 104 andDA server 106. For example, DAclient 102 ofuser device 104 can be configured to transmit information (e.g., a user request received at user device 104) to DAserver 106 viasecond user device 122. DAserver 106 can process the information and return relevant data (e.g., data content responsive to the user request) touser device 104 viasecond user device 122. - In some examples,
user device 104 can be configured to communicate abbreviated requests for data tosecond user device 122 to reduce the amount of information transmitted fromuser device 104.Second user device 122 can be configured to determine supplemental information to add to the abbreviated request to generate a complete request to transmit to DAserver 106. This system architecture can advantageously allowuser device 104 having limited communication capabilities and/or limited battery power (e.g., a watch or a similar compact electronic device) to access services provided byDA server 106 by usingsecond user device 122, having greater communication capabilities and/or battery power (e.g., a mobile phone, laptop computer, tablet computer, or the like), as a proxy toDA server 106. While only twouser devices FIG. 1 , it should be appreciated thatsystem 100 can include any number and type of user devices configured in this proxy configuration to communicate withDA server system 106. - Although the digital assistant shown in
FIG. 1 can include both a client-side portion (e.g., DA client 102) and a server-side portion (e.g., DA server 106), in some examples, the functions of a digital assistant can be implemented as a standalone application installed on a user device. In addition, the divisions of functionalities between the client and server portions of the digital assistant can vary in different implementations. For instance, in some examples, the DA client can be a thin-client that provides only user-facing input and output processing functions, and delegates all other functionalities of the digital assistant to a backend server. - Attention is now directed toward embodiments of electronic devices for implementing the client-side portion of a digital assistant.
FIG. 2A is a block diagram illustrating portablemultifunction device 200 with touch-sensitive display system 212 in accordance with some embodiments. Touch-sensitive display 212 is sometimes called a “touch screen” for convenience and is sometimes known as or called a “touch-sensitive display system.”Device 200 includes memory 202 (which optionally includes one or more computer-readable storage mediums),memory controller 222, one or more processing units (CPUs) 220, peripherals interface 218,RF circuitry 208,audio circuitry 210,speaker 211,microphone 213, input/output (I/O)subsystem 206, otherinput control devices 216, andexternal port 224.Device 200 optionally includes one or moreoptical sensors 264.Device 200 optionally includes one or morecontact intensity sensors 265 for detecting intensity of contacts on device 200 (e.g., a touch-sensitive surface such as touch-sensitive display system 212 of device 200).Device 200 optionally includes one or moretactile output generators 267 for generating tactile outputs on device 200 (e.g., generating tactile outputs on a touch-sensitive surface such as touch-sensitive display system 212 ofdevice 200 ortouchpad 455 of device 400). These components optionally communicate over one or more communication buses orsignal lines 203. - As used in the specification and claims, the term “intensity” of a contact on a touch-sensitive surface refers to the force or pressure (force per unit area) of a contact (e.g., a finger contact) on the touch-sensitive surface, or to a substitute (proxy) for the force or pressure of a contact on the touch-sensitive surface. The intensity of a contact has a range of values that includes at least four distinct values and more typically includes hundreds of distinct values (e.g., at least 256). Intensity of a contact is, optionally, determined (or measured) using various approaches and various sensors or combinations of sensors. For example, one or more force sensors underneath or adjacent to the touch-sensitive surface are, optionally, used to measure force at various points on the touch-sensitive surface. In some implementations, force measurements from multiple force sensors are combined (e.g., a weighted average) to determine an estimated force of a contact. Similarly, a pressure-sensitive tip of a stylus is, optionally, used to determine a pressure of the stylus on the touch-sensitive surface. Alternatively, the size of the contact area detected on the touch-sensitive surface and/or changes thereto, the capacitance of the touch-sensitive surface proximate to the contact and/or changes thereto, and/or the resistance of the touch-sensitive surface proximate to the contact and/or changes thereto are, optionally, used as a substitute for the force or pressure of the contact on the touch-sensitive surface. In some implementations, the substitute measurements for contact force or pressure are used directly to determine whether an intensity threshold has been exceeded (e.g., the intensity threshold is described in units corresponding to the substitute measurements). In some implementations, the substitute measurements for contact force or pressure are converted to an estimated force or pressure, and the estimated force or pressure is used to determine whether an intensity threshold has been exceeded (e.g., the intensity threshold is a pressure threshold measured in units of pressure). Using the intensity of a contact as an attribute of a user input allows for user access to additional device functionality that may otherwise not be accessible by the user on a reduced-size device with limited real estate for displaying affordances (e.g., on a touch-sensitive display) and/or receiving user input (e.g., via a touch-sensitive display, a touch-sensitive surface, or a physical/mechanical control such as a knob or a button).
- As used in the specification and claims, the term “tactile output” refers to physical displacement of a device relative to a previous position of the device, physical displacement of a component (e.g., a touch-sensitive surface) of a device relative to another component (e.g., housing) of the device, or displacement of the component relative to a center of mass of the device that will be detected by a user with the user's sense of touch. For example, in situations where the device or the component of the device is in contact with a surface of a user that is sensitive to touch (e.g., a finger, palm, or other part of a user's hand), the tactile output generated by the physical displacement will be interpreted by the user as a tactile sensation corresponding to a perceived change in physical characteristics of the device or the component of the device. For example, movement of a touch-sensitive surface (e.g., a touch-sensitive display or trackpad) is, optionally, interpreted by the user as a “down click” or “up click” of a physical actuator button. In some cases, a user will feel a tactile sensation such as an “down click” or “up click” even when there is no movement of a physical actuator button associated with the touch-sensitive surface that is physically pressed (e.g., displaced) by the user's movements. As another example, movement of the touch-sensitive surface is, optionally, interpreted or sensed by the user as “roughness” of the touch-sensitive surface, even when there is no change in smoothness of the touch-sensitive surface. While such interpretations of touch by a user will be subject to the individualized sensory perceptions of the user, there are many sensory perceptions of touch that are common to a large majority of users. Thus, when a tactile output is described as corresponding to a particular sensory perception of a user (e.g., an “up click,” a “down click,” “roughness”), unless otherwise stated, the generated tactile output corresponds to physical displacement of the device or a component thereof that will generate the described sensory perception for a typical (or average) user.
- It should be appreciated that
device 200 is only one example of a portable multifunction device, and thatdevice 200 optionally has more or fewer components than shown, optionally combines two or more components, or optionally has a different configuration or arrangement of the components. The various components shown inFIG. 2A are implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and/or application-specific integrated circuits. -
Memory 202 may include one or more computer-readable storage mediums. The computer-readable storage mediums may be tangible and non-transitory.Memory 202 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices.Memory controller 222 may control access tomemory 202 by other components ofdevice 200. - In some examples, a non-transitory computer-readable storage medium of
memory 202 can be used to store instructions (e.g., for performing aspects ofprocess 900, described below) for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. In other examples, the instructions (e.g., for performing aspects ofprocess 900, described below) can be stored on a non-transitory computer-readable storage medium (not shown) of theserver system 108 or can be divided between the non-transitory computer-readable storage medium ofmemory 202 and the non-transitory computer-readable storage medium ofserver system 108. In the context of this document, a “non-transitory computer-readable storage medium” can be any medium that can contain or store the program for use by or in connection with the instruction execution system, apparatus, or device. - Peripherals interface 218 can be used to couple input and output peripherals of the device to
CPU 220 andmemory 202. The one ormore processors 220 run or execute various software programs and/or sets of instructions stored inmemory 202 to perform various functions fordevice 200 and to process data. In some embodiments, peripherals interface 218,CPU 220, andmemory controller 222 may be implemented on a single chip, such aschip 204. In some other embodiments, they may be implemented on separate chips. - RF (radio frequency)
circuitry 208 receives and sends RF signals, also called electromagnetic signals.RF circuitry 208 converts electrical signals to/from electromagnetic signals and communicates with communications networks and other communications devices via the electromagnetic signals.RF circuitry 208 optionally includes well-known circuitry for performing these functions, including but not limited to an antenna system, an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a CODEC chipset, a subscriber identity module (SIM) card, memory, and so forth.RF circuitry 208 optionally communicates with networks, such as the Internet, also referred to as the World Wide Web (WWW), an intranet and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN) and/or a metropolitan area network (MAN), and other devices by wireless communication. TheRF circuitry 208 optionally includes well-known circuitry for detecting near field communication (NFC) fields, such as by a short-range communication radio. The wireless communication optionally uses any of a plurality of communications standards, protocols, and technologies, including but not limited to Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), high-speed downlink packet access (HSDPA), high-speed uplink packet access (HSUPA), Evolution, Data-Only (EV-DO), HSPA, HSPA+, Dual-Cell HSPA (DC-HSPDA), long term evolution (LTE), near field communication (NFC), wideband code division multiple access (W-CDMA), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Bluetooth Low Energy (BTLE), Wireless Fidelity (Wi-Fi) (e.g., IEEE 802.11a, IEEE 802.11b, IEEE 802.11g, IEEE 802.11n, and/or IEEE 802.11ac), voice over Internet Protocol (VoIP), Wi-MAX, a protocol for e mail (e.g., Internet message access protocol (IMAP) and/or post office protocol (POP)), instant messaging (e.g., extensible messaging and presence protocol (XMPP), Session Initiation Protocol for Instant Messaging and Presence Leveraging Extensions (SIMPLE), Instant Messaging and Presence Service (IMPS)), and/or Short Message Service (SMS), or any other suitable communication protocol, including communication protocols not yet developed as of the filing date of this document. -
Audio circuitry 210,speaker 211, andmicrophone 213 provide an audio interface between a user anddevice 200.Audio circuitry 210 receives audio data fromperipherals interface 218, converts the audio data to an electrical signal, and transmits the electrical signal tospeaker 211.Speaker 211 converts the electrical signal to human-audible sound waves.Audio circuitry 210 also receives electrical signals converted bymicrophone 213 from sound waves.Audio circuitry 210 converts the electrical signal to audio data and transmits the audio data to peripherals interface 218 for processing. Audio data may be retrieved from and/or transmitted tomemory 202 and/orRF circuitry 208 byperipherals interface 218. In some embodiments,audio circuitry 210 also includes a headset jack (e.g., 312,FIG. 3 ). The headset jack provides an interface betweenaudio circuitry 210 and removable audio input/output peripherals, such as output-only headphones or a headset with both output (e.g., a headphone for one or both ears) and input (e.g., a microphone). - I/
O subsystem 206 couples input/output peripherals ondevice 200, such astouch screen 212 and otherinput control devices 216, toperipherals interface 218. I/O subsystem 206 optionally includesdisplay controller 256,optical sensor controller 258,intensity sensor controller 259,haptic feedback controller 261, and one ormore input controllers 260 for other input or control devices. The one ormore input controllers 260 receive/send electrical signals from/to otherinput control devices 216. The otherinput control devices 216 optionally include physical buttons (e.g., push buttons, rocker buttons, etc.), dials, slider switches, joysticks, click wheels, and so forth. In some alternate embodiments, input controller(s) 260 are, optionally, coupled to any (or none) of the following: a keyboard, an infrared port, a USB port, and a pointer device such as a mouse. The one or more buttons (e.g., 308,FIG. 3 ) optionally include an up/down button for volume control ofspeaker 211 and/ormicrophone 213. The one or more buttons optionally include a push button (e.g., 306,FIG. 3 ). - A quick press of the push button may disengage a lock of
touch screen 212 or begin a process that uses gestures on the touch screen to unlock the device, as described in U.S. patent application Ser. No. 11/322,549, “Unlocking a Device by Performing Gestures on an Unlock Image,” filed Dec. 23, 2005, U.S. Pat. No. 7,657,849, which is hereby incorporated by reference in its entirety. A longer press of the push button (e.g., 306) may turn power todevice 200 on or off. The user may be able to customize a functionality of one or more of the buttons.Touch screen 212 is used to implement virtual or soft buttons and one or more soft keyboards. - Touch-
sensitive display 212 provides an input interface and an output interface between the device and a user.Display controller 256 receives and/or sends electrical signals from/totouch screen 212.Touch screen 212 displays visual output to the user. The visual output may include graphics, text, icons, video, and any combination thereof (collectively termed “graphics”). In some embodiments, some or all of the visual output may correspond to user-interface objects. -
Touch screen 212 has a touch-sensitive surface, sensor, or set of sensors that accepts input from the user based on haptic and/or tactile contact.Touch screen 212 and display controller 256 (along with any associated modules and/or sets of instructions in memory 202) detect contact (and any movement or breaking of the contact) ontouch screen 212 and convert the detected contact into interaction with user-interface objects (e.g., one or more soft keys, icons, web pages, or images) that are displayed ontouch screen 212. In an exemplary embodiment, a point of contact betweentouch screen 212 and the user corresponds to a finger of the user. -
Touch screen 212 may use LCD (liquid crystal display) technology, LPD (light emitting polymer display) technology, or LED (light emitting diode) technology, although other display technologies may be used in other embodiments.Touch screen 212 anddisplay controller 256 may detect contact and any movement or breaking thereof using any of a plurality of touch sensing technologies now known or later developed, including but not limited to capacitive, resistive, infrared, and surface acoustic wave technologies, as well as other proximity sensor arrays or other elements for determining one or more points of contact withtouch screen 212. In an exemplary embodiment, projected mutual capacitance sensing technology is used, such as that found in the iPhone® and iPod Touch® from Apple Inc. of Cupertino, Calif. - A touch-sensitive display in some embodiments of
touch screen 212 may be analogous to the multi-touch sensitive touchpads described in the following U.S. Pat. No. 6,323,846 (Westerman et al.), U.S. Pat. No. 6,570,557 (Westerman et al.), and/or U.S. Pat. No. 6,677,932 (Westerman), and/or U.S. Patent Publication 2002/0015024A1, each of which is hereby incorporated by reference in its entirety. However,touch screen 212 displays visual output fromdevice 200, whereas touch-sensitive touchpads do not provide visual output. - A touch-sensitive display in some embodiments of
touch screen 212 may be as described in the following applications: (1) U.S. patent application Ser. No. 11/381,313, “Multipoint Touch Surface Controller,” filed May 2, 2006; (2) U.S. patent application Ser. No. 10/840,862, “Multipoint Touchscreen,” filed May 6, 2004; (3) U.S. patent application Ser. No. 10/903,964, “Gestures For Touch Sensitive Input Devices,” filed Jul. 30, 2004; (4) U.S. patent application Ser. No. 11/048,264, “Gestures For Touch Sensitive Input Devices,” filed Jan. 31, 2005; (5) U.S. patent application Ser. No. 11/038,590, “Mode-Based Graphical User Interfaces For Touch Sensitive Input Devices,” filed Jan. 18, 2005; (6) U.S. patent application Ser. No. 11/228,758, “Virtual Input Device Placement On A Touch Screen User Interface,” filed Sep. 16, 2005; (7) U.S. patent application Ser. No. 11/228,700, “Operation Of A Computer With A Touch Screen Interface,” filed Sep. 16, 2005; (8) U.S. patent application Ser. No. 11/228,737, “Activating Virtual Keys Of A Touch-Screen Virtual Keyboard,” filed Sep. 16, 2005; and (9) U.S. patent application Ser. No. 11/367,749, “Multi-Functional Hand-Held Device,” filed Mar. 3, 2006. All of these applications are incorporated by reference herein in their entirety. -
Touch screen 212 may have a video resolution in excess of 100 dpi. In some embodiments, the touch screen has a video resolution of approximately 160 dpi. The user may make contact withtouch screen 212 using any suitable object or appendage, such as a stylus, a finger, and so forth. In some embodiments, the user interface is designed to work primarily with finger-based contacts and gestures, which can be less precise than stylus-based input due to the larger area of contact of a finger on the touch screen. In some embodiments, the device translates the rough finger-based input into a precise pointer/cursor position or command for performing the actions desired by the user. - In some embodiments, in addition to the touch screen,
device 200 may include a touchpad (not shown) for activating or deactivating particular functions. In some embodiments, the touchpad is a touch-sensitive area of the device that, unlike the touch screen, does not display visual output. The touchpad may be a touch-sensitive surface that is separate fromtouch screen 212 or an extension of the touch-sensitive surface formed by the touch screen. -
Device 200 also includespower system 262 for powering the various components.Power system 262 may include a power management system, one or more power sources (e.g., battery, alternating current (AC)), a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator (e.g., a light-emitting diode (LED)) and any other components associated with the generation, management and distribution of power in portable devices. -
Device 200 may also include one or moreoptical sensors 264.FIG. 2A shows an optical sensor coupled tooptical sensor controller 258 in I/O subsystem 206.Optical sensor 264 may include charge-coupled device (CCD) or complementary metal-oxide semiconductor (CMOS) phototransistors.Optical sensor 264 receives light from the environment, projected through one or more lenses, and converts the light to data representing an image. In conjunction with imaging module 243 (also called a camera module),optical sensor 264 may capture still images or video. In some embodiments, an optical sensor is located on the back ofdevice 200, oppositetouch screen display 212 on the front of the device so that the touch screen display may be used as a viewfinder for still and/or video image acquisition. In some embodiments, an optical sensor is located on the front of the device so that the user's image may be obtained for video conferencing while the user views the other video conference participants on the touch screen display. In some embodiments, the position ofoptical sensor 264 can be changed by the user (e.g., by rotating the lens and the sensor in the device housing) so that a singleoptical sensor 264 may be used along with the touch screen display for both video conferencing and still and/or video image acquisition. -
Device 200 optionally also includes one or morecontact intensity sensors 265.FIG. 2A shows a contact intensity sensor coupled tointensity sensor controller 259 in I/O subsystem 206.Contact intensity sensor 265 optionally includes one or more piezoresistive strain gauges, capacitive force sensors, electric force sensors, piezoelectric force sensors, optical force sensors, capacitive touch-sensitive surfaces, or other intensity sensors (e.g., sensors used to measure the force (or pressure) of a contact on a touch-sensitive surface).Contact intensity sensor 265 receives contact intensity information (e.g., pressure information or a proxy for pressure information) from the environment. In some embodiments, at least one contact intensity sensor is collocated with, or proximate to, a touch-sensitive surface (e.g., touch-sensitive display system 212). In some embodiments, at least one contact intensity sensor is located on the back ofdevice 200, oppositetouch screen display 212, which is located on the front ofdevice 200. -
Device 200 may also include one ormore proximity sensors 266.FIG. 2A showsproximity sensor 266 coupled toperipherals interface 218. Alternately,proximity sensor 266 may be coupled toinput controller 260 in I/O subsystem 206.Proximity sensor 266 may perform as described in U.S. patent application Ser. No. 11/241,839, “Proximity Detector In Handheld Device”; Ser. No. 11/240,788, “Proximity Detector In Handheld Device”; Ser. No. 11/620,702, “Using Ambient Light Sensor To Augment Proximity Sensor Output”; Ser. No. 11/586,862, “Automated Response To And Sensing Of User Activity In Portable Devices”; and Ser. No. 11/638,251, “Methods And Systems For Automatic Configuration Of Peripherals,” which are hereby incorporated by reference in their entirety. In some embodiments, the proximity sensor turns off and disablestouch screen 212 when the multifunction device is placed near the user's ear (e.g., when the user is making a phone call). -
Device 200 optionally also includes one or moretactile output generators 267.FIG. 2A shows a tactile output generator coupled tohaptic feedback controller 261 in I/O subsystem 206.Tactile output generator 267 optionally includes one or more electroacoustic devices such as speakers or other audio components and/or electromechanical devices that convert energy into linear motion such as a motor, solenoid, electroactive polymer, piezoelectric actuator, electrostatic actuator, or other tactile output generating component (e.g., a component that converts electrical signals into tactile outputs on the device).Contact intensity sensor 265 receives tactile feedback generation instructions fromhaptic feedback module 233 and generates tactile outputs ondevice 200 that are capable of being sensed by a user ofdevice 200. In some embodiments, at least one tactile output generator is collocated with, or proximate to, a touch-sensitive surface (e.g., touch-sensitive display system 212) and, optionally, generates a tactile output by moving the touch-sensitive surface vertically (e.g., in/out of a surface of device 200) or laterally (e.g., back and forth in the same plane as a surface of device 200). In some embodiments, at least one tactile output generator sensor is located on the back ofdevice 200, oppositetouch screen display 212, which is located on the front ofdevice 200. -
Device 200 may also include one ormore accelerometers 268.FIG. 2A showsaccelerometer 268 coupled toperipherals interface 218. Alternately,accelerometer 268 may be coupled to aninput controller 260 in I/O subsystem 206.Accelerometer 268 may perform as described in U.S. Patent Publication No. 20050190059, “Acceleration-based Theft Detection System for Portable Electronic Devices,” and U.S. Patent Publication No. 20060017692, “Methods And Apparatuses For Operating A Portable Device Based On An Accelerometer,” both of which are incorporated by reference herein in their entirety. In some embodiments, information is displayed on the touch screen display in a portrait view or a landscape view based on an analysis of data received from the one or more accelerometers.Device 200 optionally includes, in addition to accelerometer(s) 268, a magnetometer (not shown) and a GPS (or GLONASS or other global navigation system) receiver (not shown) for obtaining information concerning the location and orientation (e.g., portrait or landscape) ofdevice 200. - In some embodiments, the software components stored in
memory 202 includeoperating system 226, communication module (or set of instructions) 228, contact/motion module (or set of instructions) 230, graphics module (or set of instructions) 232, text input module (or set of instructions) 234, Global Positioning System (GPS) module (or set of instructions) 235, DigitalAssistant Client Module 229, and applications (or sets of instructions) 236. Further,memory 202 can store data and models, such as user data andmodels 231. Furthermore, in some embodiments, memory 202 (FIG. 2A ) or 470 (FIG. 4 ) stores device/globalinternal state 257, as shown inFIGS. 2A and 4 . Device/globalinternal state 257 includes one or more of: active application state, indicating which applications, if any, are currently active; display state, indicating what applications, views or other information occupy various regions oftouch screen display 212; sensor state, including information obtained from the device's various sensors andinput control devices 216; and location information concerning the device's location and/or attitude. - Operating system 226 (e.g., Darwin, RTXC, LINUX, UNIX, OS X, iOS, WINDOWS, or an embedded operating system such as VxWorks) includes various software components and/or drivers for controlling and managing general system tasks (e.g., memory management, storage device control, power management, etc.) and facilitates communication between various hardware and software components.
-
Communication module 228 facilitates communication with other devices over one or moreexternal ports 224 and also includes various software components for handling data received byRF circuitry 208 and/orexternal port 224. External port 224 (e.g., Universal Serial Bus (USB), FIREWIRE, etc.) is adapted for coupling directly to other devices or indirectly over a network (e.g., the Internet, wireless LAN, etc.). In some embodiments, the external port is a multi-pin (e.g., 30-pin) connector that is the same as, or similar to and/or compatible with, the 30-pin connector used on iPod® (trademark of Apple Inc.) devices. - Contact/
motion module 230 optionally detects contact with touch screen 212 (in conjunction with display controller 256) and other touch-sensitive devices (e.g., a touchpad or physical click wheel). Contact/motion module 230 includes various software components for performing various operations related to detection of contact, such as determining if contact has occurred (e.g., detecting a finger-down event), determining an intensity of the contact (e.g., the force or pressure of the contact or a substitute for the force or pressure of the contact), determining if there is movement of the contact and tracking the movement across the touch-sensitive surface (e.g., detecting one or more finger-dragging events), and determining if the contact has ceased (e.g., detecting a finger-up event or a break in contact). Contact/motion module 230 receives contact data from the touch-sensitive surface. Determining movement of the point of contact, which is represented by a series of contact data, optionally includes determining speed (magnitude), velocity (magnitude and direction), and/or an acceleration (a change in magnitude and/or direction) of the point of contact. These operations are, optionally, applied to single contacts (e.g., one finger contacts) or to multiple simultaneous contacts (e.g., “multitouch”/multiple finger contacts). In some embodiments, contact/motion module 230 anddisplay controller 256 detect contact on a touchpad. - In some embodiments, contact/
motion module 230 uses a set of one or more intensity thresholds to determine whether an operation has been performed by a user (e.g., to determine whether a user has “clicked” on an icon). In some embodiments, at least a subset of the intensity thresholds are determined in accordance with software parameters (e.g., the intensity thresholds are not determined by the activation thresholds of particular physical actuators and can be adjusted without changing the physical hardware of device 200). For example, a mouse “click” threshold of a trackpad or touch screen display can be set to any of a large range of predefined threshold values without changing the trackpad or touch screen display hardware. Additionally, in some implementations, a user of the device is provided with software settings for adjusting one or more of the set of intensity thresholds (e.g., by adjusting individual intensity thresholds and/or by adjusting a plurality of intensity thresholds at once with a system-level click “intensity” parameter). - Contact/
motion module 230 optionally detects a gesture input by a user. Different gestures on the touch-sensitive surface have different contact patterns (e.g., different motions, timings, and/or intensities of detected contacts). Thus, a gesture is, optionally, detected by detecting a particular contact pattern. For example, detecting a finger tap gesture includes detecting a finger-down event followed by detecting a finger-up (liftoff) event at the same position (or substantially the same position) as the finger-down event (e.g., at the position of an icon). As another example, detecting a finger swipe gesture on the touch-sensitive surface includes detecting a finger-down event followed by detecting one or more finger-dragging events, and subsequently followed by detecting a finger-up (liftoff) event. -
Graphics module 232 includes various known software components for rendering and displaying graphics ontouch screen 212 or other display, including components for changing the visual impact (e.g., brightness, transparency, saturation, contrast, or other visual property) of graphics that are displayed. As used herein, the term “graphics” includes any object that can be displayed to a user, including, without limitation, text, web pages, icons (such as user-interface objects including soft keys), digital images, videos, animations, and the like. - In some embodiments,
graphics module 232 stores data representing graphics to be used. Each graphic is, optionally, assigned a corresponding code.Graphics module 232 receives, from applications etc., one or more codes specifying graphics to be displayed along with, if necessary, coordinate data and other graphic property data, and then generates screen image data to output to displaycontroller 256. -
Haptic feedback module 233 includes various software components for generating instructions used by tactile output generator(s) 267 to produce tactile outputs at one or more locations ondevice 200 in response to user interactions withdevice 200. -
Text input module 234, which may be a component ofgraphics module 232, provides soft keyboards for entering text in various applications (e.g.,contacts 237,e mail 240,IM 241,browser 247, and any other application that needs text input). -
GPS module 235 determines the location of the device and provides this information for use in various applications (e.g., to telephone 238 for use in location-based dialing; tocamera 243 as picture/video metadata; and to applications that provide location-based services such as weather widgets, local yellow page widgets, and map/navigation widgets). - Digital
assistant client module 229 can include various client-side digital assistant instructions to provide the client-side functionalities of the digital assistant. For example, digitalassistant client module 229 can be capable of accepting voice input (e.g., speech input), text input, touch input, and/or gestural input through various user interfaces (e.g.,microphone 213, accelerometer(s) 268, touch-sensitive display system 212, optical sensor(s) 229, otherinput control devices 216, etc.) of portablemultifunction device 200. Digitalassistant client module 229 can also be capable of providing output in audio (e.g., speech output), visual, and/or tactile forms through various output interfaces (e.g.,speaker 211, touch-sensitive display system 212, tactile output generator(s) 267, etc.) of portablemultifunction device 200. For example, output can be provided as voice, sound, alerts, text messages, menus, graphics, videos, animations, vibrations, and/or combinations of two or more of the above. During operation, digitalassistant client module 229 can communicate withDA server 106 usingRF circuitry 208. - User data and
models 231 can include various data associated with the user (e.g., user-specific vocabulary data, user preference data, user-specified name pronunciations, data from the user's electronic address book, to-do lists, shopping lists, etc.) to provide the client-side functionalities of the digital assistant. Further, user data andmodels 231 can includes various models (e.g., speech recognition models, statistical language models, natural language processing models, ontology, task flow models, service models, etc.) for processing user input and determining user intent. - In some examples, digital
assistant client module 229 can utilize the various sensors, subsystems, and peripheral devices of portablemultifunction device 200 to gather additional information from the surrounding environment of theportable multifunction device 200 to establish a context associated with a user, the current user interaction, and/or the current user input. In some examples, digitalassistant client module 229 can provide the contextual information or a subset thereof with the user input toDA server 106 to help infer the user's intent. In some examples, the digital assistant can also use the contextual information to determine how to prepare and deliver outputs to the user. Contextual information can be referred to as context data. - In some examples, the contextual information that accompanies the user input can include sensor information, e.g., lighting, ambient noise, ambient temperature, images or videos of the surrounding environment, etc. In some examples, the contextual information can also include the physical state of the device, e.g., device orientation, device location, device temperature, power level, speed, acceleration, motion patterns, cellular signals strength, etc. In some examples, information related to the software state of
DA server 106, e.g., running processes, installed programs, past and present network activities, background services, error logs, resources usage, etc., and of portablemultifunction device 200 can be provided toDA server 106 as contextual information associated with a user input. - In some examples, the digital
assistant client module 229 can selectively provide information (e.g., user data 231) stored on theportable multifunction device 200 in response to requests fromDA server 106. In some examples, digitalassistant client module 229 can also elicit additional input from the user via a natural language dialogue or other user interfaces upon request byDA server 106. Digitalassistant client module 229 can pass the additional input toDA server 106 to helpDA server 106 in intent deduction and/or fulfillment of the user's intent expressed in the user request. - A more detailed description of a digital assistant is described below with reference to
FIGS. 7A-C . It should be recognized that digitalassistant client module 229 can include any number of the sub-modules ofdigital assistant module 726 described below. -
Applications 236 may include the following modules (or sets of instructions), or a subset or superset thereof: -
- Contacts module 237 (sometimes called an address book or contact list);
-
Telephone module 238; -
Video conference module 239; -
E-mail client module 240; - Instant messaging (IM)
module 241; -
Workout support module 242; -
Camera module 243 for still and/or video images; -
Image management module 244; - Video player module;
- Music player module;
-
Browser module 247; -
Calendar module 248; -
Widget modules 249, which may include one or more of: weather widget 249-1, stocks widget 249-2, calculator widget 249-3, alarm clock widget 249-4, dictionary widget 249-5, and other widgets obtained by the user, as well as user-created widgets 249-6; -
Widget creator module 250 for making user-created widgets 249-6; -
Search module 251; - Video and
music player module 252, which merges video player module and music player module; -
Notes module 253; -
Map module 254; and/or -
Online video module 255.
- Examples of
other applications 236 that may be stored inmemory 202 include other word processing applications, other image editing applications, drawing applications, presentation applications, JAVA-enabled applications, encryption, digital rights management, voice recognition, and voice replication. - In conjunction with
touch screen 212,display controller 256, contact/motion module 230,graphics module 232, andtext input module 234,contacts module 237 may be used to manage an address book or contact list (e.g., stored in applicationinternal state 292 ofcontacts module 237 inmemory 202 or memory 470), including: adding name(s) to the address book; deleting name(s) from the address book; associating telephone number(s), e-mail address(es), physical address(es) or other information with a name; associating an image with a name; categorizing and sorting names; providing telephone numbers or e-mail addresses to initiate and/or facilitate communications bytelephone 238,video conference module 239,e-mail 240, orIM 241; and so forth. - In conjunction with
RF circuitry 208,audio circuitry 210,speaker 211,microphone 213,touch screen 212,display controller 256, contact/motion module 230,graphics module 232, andtext input module 234,telephone module 238 may be used to enter a sequence of characters corresponding to a telephone number, access one or more telephone numbers incontacts module 237, modify a telephone number that has been entered, dial a respective telephone number, conduct a conversation, and disconnect or hang up when the conversation is completed. As noted above, the wireless communication may use any of a plurality of communications standards, protocols, and technologies. - In conjunction with
RF circuitry 208,audio circuitry 210,speaker 211,microphone 213,touch screen 212,display controller 256,optical sensor 264,optical sensor controller 258, contact/motion module 230,graphics module 232,text input module 234,contacts module 237, andtelephone module 238,video conference module 239 includes executable instructions to initiate, conduct, and terminate a video conference between a user and one or more other participants in accordance with user instructions. - In conjunction with
RF circuitry 208,touch screen 212,display controller 256, contact/motion module 230,graphics module 232, andtext input module 234,e-mail client module 240 includes executable instructions to create, send, receive, and manage e-mail in response to user instructions. In conjunction withimage management module 244,e-mail client module 240 makes it very easy to create and send e-mails with still or video images taken withcamera module 243. - In conjunction with
RF circuitry 208,touch screen 212,display controller 256, contact/motion module 230,graphics module 232, andtext input module 234, theinstant messaging module 241 includes executable instructions to enter a sequence of characters corresponding to an instant message, to modify previously entered characters, to transmit a respective instant message (for example, using a Short Message Service (SMS) or Multimedia Message Service (MMS) protocol for telephony-based instant messages or using XMPP, SIMPLE, or IMPS for Internet-based instant messages), to receive instant messages, and to view received instant messages. In some embodiments, transmitted and/or received instant messages may include graphics, photos, audio files, video files and/or other attachments as are supported in an MMS and/or an Enhanced Messaging Service (EMS). As used herein, “instant messaging” refers to both telephony-based messages (e.g., messages sent using SMS or MMS) and Internet-based messages (e.g., messages sent using XMPP, SIMPLE, or IMPS). - In conjunction with
RF circuitry 208,touch screen 212,display controller 256, contact/motion module 230,graphics module 232,text input module 234,GPS module 235,map module 254, and music player module,workout support module 242 includes executable instructions to create workouts (e.g., with time, distance, and/or calorie burning goals); communicate with workout sensors (sports devices); receive workout sensor data; calibrate sensors used to monitor a workout; select and play music for a workout; and display, store, and transmit workout data. - In conjunction with
touch screen 212,display controller 256, optical sensor(s) 264,optical sensor controller 258, contact/motion module 230,graphics module 232, andimage management module 244,camera module 243 includes executable instructions to capture still images or video (including a video stream) and store them intomemory 202, modify characteristics of a still image or video, or delete a still image or video frommemory 202. - In conjunction with
touch screen 212,display controller 256, contact/motion module 230,graphics module 232,text input module 234, andcamera module 243,image management module 244 includes executable instructions to arrange, modify (e.g., edit), or otherwise manipulate, label, delete, present (e.g., in a digital slide show or album), and store still and/or video images. - In conjunction with
RF circuitry 208,touch screen 212,display controller 256, contact/motion module 230,graphics module 232, andtext input module 234,browser module 247 includes executable instructions to browse the Internet in accordance with user instructions, including searching, linking to, receiving, and displaying web pages or portions thereof, as well as attachments and other files linked to web pages. - In conjunction with
RF circuitry 208,touch screen 212,display controller 256, contact/motion module 230,graphics module 232,text input module 234,e-mail client module 240, andbrowser module 247,calendar module 248 includes executable instructions to create, display, modify, and store calendars and data associated with calendars (e.g., calendar entries, to-do lists, etc.) in accordance with user instructions. - In conjunction with
RF circuitry 208,touch screen 212,display controller 256, contact/motion module 230,graphics module 232,text input module 234, andbrowser module 247,widget modules 249 are mini-applications that may be downloaded and used by a user (e.g., weather widget 249-1, stocks widget 249-2, calculator widget 249-3, alarm clock widget 249-4, and dictionary widget 249-5) or created by the user (e.g., user-created widget 249-6). In some embodiments, a widget includes an HTML (Hypertext Markup Language) file, a CSS (Cascading Style Sheets) file, and a JavaScript file. In some embodiments, a widget includes an XML (Extensible Markup Language) file and a JavaScript file (e.g., Yahoo! Widgets). - In conjunction with
RF circuitry 208,touch screen 212,display controller 256, contact/motion module 230,graphics module 232,text input module 234, andbrowser module 247, thewidget creator module 250 may be used by a user to create widgets (e.g., turning a user-specified portion of a web page into a widget). - In conjunction with
touch screen 212,display controller 256, contact/motion module 230,graphics module 232, andtext input module 234,search module 251 includes executable instructions to search for text, music, sound, image, video, and/or other files inmemory 202 that match one or more search criteria (e.g., one or more user-specified search terms) in accordance with user instructions. - In conjunction with
touch screen 212,display controller 256, contact/motion module 230,graphics module 232,audio circuitry 210,speaker 211,RF circuitry 208, andbrowser module 247, video andmusic player module 252 includes executable instructions that allow the user to download and play back recorded music and other sound files stored in one or more file formats, such as MP3 or AAC files, and executable instructions to display, present, or otherwise play back videos (e.g., ontouch screen 212 or on an external, connected display via external port 224). In some embodiments,device 200 optionally includes the functionality of an MP3 player, such as an iPod (trademark of Apple Inc.). - In conjunction with
touch screen 212,display controller 256, contact/motion module 230,graphics module 232, andtext input module 234, notesmodule 253 includes executable instructions to create and manage notes, to-do lists, and the like in accordance with user instructions. - In conjunction with
RF circuitry 208,touch screen 212,display controller 256, contact/motion module 230,graphics module 232,text input module 234,GPS module 235, andbrowser module 247,map module 254 may be used to receive, display, modify, and store maps and data associated with maps (e.g., driving directions, data on stores and other points of interest at or near a particular location, and other location-based data) in accordance with user instructions. - In conjunction with
touch screen 212,display controller 256, contact/motion module 230,graphics module 232,audio circuitry 210,speaker 211,RF circuitry 208,text input module 234,e-mail client module 240, andbrowser module 247,online video module 255 includes instructions that allow the user to access, browse, receive (e.g., by streaming and/or download), play back (e.g., on the touch screen or on an external, connected display via external port 224), send an e-mail with a link to a particular online video, and otherwise manage online videos in one or more file formats, such as H.264. In some embodiments,instant messaging module 241, rather thane-mail client module 240, is used to send a link to a particular online video. Additional description of the online video application can be found in U.S. Provisional Patent Application No. 60/936,562, “Portable Multifunction Device, Method, and Graphical User Interface for Playing Online Videos,” filed Jun. 20, 2007, and U.S. patent application Ser. No. 11/968,067, “Portable Multifunction Device, Method, and Graphical User Interface for Playing Online Videos,” filed Dec. 31, 2007, the contents of which are hereby incorporated by reference in their entirety. - Each of the above-identified modules and applications corresponds to a set of executable instructions for performing one or more functions described above and the methods described in this application (e.g., the computer-implemented methods and other information processing methods described herein). These modules (e.g., sets of instructions) need not be implemented as separate software programs, procedures, or modules, and thus various subsets of these modules may be combined or otherwise rearranged in various embodiments. For example, video player module may be combined with music player module into a single module (e.g., video and
music player module 252,FIG. 2A ). In some embodiments,memory 202 may store a subset of the modules and data structures identified above. Furthermore,memory 202 may store additional modules and data structures not described above. - In some embodiments,
device 200 is a device where operation of a predefined set of functions on the device is performed exclusively through a touch screen and/or a touchpad. By using a touch screen and/or a touchpad as the primary input control device for operation ofdevice 200, the number of physical input control devices (such as push buttons, dials, and the like) ondevice 200 may be reduced. - The predefined set of functions that are performed exclusively through a touch screen and/or a touchpad optionally include navigation between user interfaces. In some embodiments, the touchpad, when touched by the user, navigates
device 200 to a main, home, or root menu from any user interface that is displayed ondevice 200. In such embodiments, a “menu button” is implemented using a touchpad. In some other embodiments, the menu button is a physical push button or other physical input control device instead of a touchpad. -
FIG. 2B is a block diagram illustrating exemplary components for event handling in accordance with some embodiments. In some embodiments, memory 202 (FIG. 2A ) or 470 (FIG. 4 ) includes event sorter 270 (e.g., in operating system 226) and a respective application 236-1 (e.g., any of the aforementioned applications 237-251, 255, 480-490). -
Event sorter 270 receives event information and determines the application 236-1 andapplication view 291 of application 236-1 to which to deliver the event information.Event sorter 270 includes event monitor 271 andevent dispatcher module 274. In some embodiments, application 236-1 includes applicationinternal state 292, which indicates the current application view(s) displayed on touch-sensitive display 212 when the application is active or executing. In some embodiments, device/globalinternal state 257 is used byevent sorter 270 to determine which application(s) is (are) currently active, and applicationinternal state 292 is used byevent sorter 270 to determineapplication views 291 to which to deliver event information. - In some embodiments, application
internal state 292 includes additional information, such as one or more of: resume information to be used when application 236-1 resumes execution, user interface state information that indicates information being displayed or that is ready for display by application 236-1, a state queue for enabling the user to go back to a prior state or view of application 236-1, and a redo/undo queue of previous actions taken by the user. -
Event monitor 271 receives event information fromperipherals interface 218. Event information includes information about a sub-event (e.g., a user touch on touch-sensitive display 212, as part of a multi-touch gesture). Peripherals interface 218 transmits information it receives from I/O subsystem 206 or a sensor, such asproximity sensor 266, accelerometer(s) 268, and/or microphone 213 (through audio circuitry 210). Information that peripherals interface 218 receives from I/O subsystem 206 includes information from touch-sensitive display 212 or a touch-sensitive surface. - In some embodiments, event monitor 271 sends requests to the peripherals interface 218 at predetermined intervals. In response, peripherals interface 218 transmits event information. In other embodiments, peripherals interface 218 transmits event information only when there is a significant event (e.g., receiving an input above a predetermined noise threshold and/or for more than a predetermined duration).
- In some embodiments,
event sorter 270 also includes a hitview determination module 272 and/or an active eventrecognizer determination module 273. - Hit
view determination module 272 provides software procedures for determining where a sub-event has taken place within one or more views when touch-sensitive display 212 displays more than one view. Views are made up of controls and other elements that a user can see on the display. - Another aspect of the user interface associated with an application is a set of views, sometimes herein called application views or user interface windows, in which information is displayed and touch-based gestures occur. The application views (of a respective application) in which a touch is detected may correspond to programmatic levels within a programmatic or view hierarchy of the application. For example, the lowest level view in which a touch is detected may be called the hit view, and the set of events that are recognized as proper inputs may be determined based, at least in part, on the hit view of the initial touch that begins a touch-based gesture.
- Hit
view determination module 272 receives information related to sub events of a touch-based gesture. When an application has multiple views organized in a hierarchy, hitview determination module 272 identifies a hit view as the lowest view in the hierarchy which should handle the sub-event. In most circumstances, the hit view is the lowest level view in which an initiating sub-event occurs (e.g., the first sub-event in the sequence of sub-events that form an event or potential event). Once the hit view is identified by the hitview determination module 272, the hit view typically receives all sub-events related to the same touch or input source for which it was identified as the hit view. - Active event
recognizer determination module 273 determines which view or views within a view hierarchy should receive a particular sequence of sub-events. In some embodiments, active eventrecognizer determination module 273 determines that only the hit view should receive a particular sequence of sub-events. In other embodiments, active eventrecognizer determination module 273 determines that all views that include the physical location of a sub-event are actively involved views, and therefore determines that all actively involved views should receive a particular sequence of sub-events. In other embodiments, even if touch sub-events were entirely confined to the area associated with one particular view, views higher in the hierarchy would still remain as actively involved views. -
Event dispatcher module 274 dispatches the event information to an event recognizer (e.g., event recognizer 280). In embodiments including active eventrecognizer determination module 273,event dispatcher module 274 delivers the event information to an event recognizer determined by active eventrecognizer determination module 273. In some embodiments,event dispatcher module 274 stores in an event queue the event information, which is retrieved by arespective event receiver 282. - In some embodiments,
operating system 226 includesevent sorter 270. Alternatively, application 236-1 includesevent sorter 270. In yet other embodiments,event sorter 270 is a stand-alone module, or a part of another module stored inmemory 202, such as contact/motion module 230. - In some embodiments, application 236-1 includes a plurality of
event handlers 290 and one or more application views 291, each of which includes instructions for handling touch events that occur within a respective view of the application's user interface. Eachapplication view 291 of the application 236-1 includes one ormore event recognizers 280. Typically, arespective application view 291 includes a plurality ofevent recognizers 280. In other embodiments, one or more ofevent recognizers 280 are part of a separate module, such as a user interface kit (not shown) or a higher level object from which application 236-1 inherits methods and other properties. In some embodiments, arespective event handler 290 includes one or more of:data updater 276,object updater 277,GUI updater 278, and/orevent data 279 received fromevent sorter 270.Event handler 290 may utilize or calldata updater 276,object updater 277, orGUI updater 278 to update the applicationinternal state 292. Alternatively, one or more of the application views 291 include one or morerespective event handlers 290. Also, in some embodiments, one or more ofdata updater 276,object updater 277, andGUI updater 278 are included in arespective application view 291. - A
respective event recognizer 280 receives event information (e.g., event data 279) fromevent sorter 270 and identifies an event from the event information.Event recognizer 280 includesevent receiver 282 andevent comparator 284. In some embodiments,event recognizer 280 also includes at least a subset of:metadata 283, and event delivery instructions 288 (which may include sub-event delivery instructions). -
Event receiver 282 receives event information fromevent sorter 270. The event information includes information about a sub-event, for example, a touch or a touch movement. Depending on the sub-event, the event information also includes additional information, such as location of the sub-event. When the sub-event concerns motion of a touch, the event information may also include speed and direction of the sub-event. In some embodiments, events include rotation of the device from one orientation to another (e.g., from a portrait orientation to a landscape orientation, or vice versa), and the event information includes corresponding information about the current orientation (also called device attitude) of the device. -
Event comparator 284 compares the event information to predefined event or sub-event definitions and, based on the comparison, determines an event or sub event, or determines or updates the state of an event or sub-event. In some embodiments,event comparator 284 includesevent definitions 286.Event definitions 286 contain definitions of events (e.g., predefined sequences of sub-events), for example, event 1 (287-1), event 2 (287-2), and others. In some embodiments, sub-events in an event (287) include, for example, touch begin, touch end, touch movement, touch cancellation, and multiple touching. In one example, the definition for event 1 (287-1) is a double tap on a displayed object. The double tap, for example, comprises a first touch (touch begin) on the displayed object for a predetermined phase, a first liftoff (touch end) for a predetermined phase, a second touch (touch begin) on the displayed object for a predetermined phase, and a second liftoff (touch end) for a predetermined phase. In another example, the definition for event 2 (287-2) is a dragging on a displayed object. The dragging, for example, comprises a touch (or contact) on the displayed object for a predetermined phase, a movement of the touch across touch-sensitive display 212, and liftoff of the touch (touch end). In some embodiments, the event also includes information for one or more associatedevent handlers 290. - In some embodiments, event definition 287 includes a definition of an event for a respective user-interface object. In some embodiments,
event comparator 284 performs a hit test to determine which user-interface object is associated with a sub-event. For example, in an application view in which three user-interface objects are displayed on touch-sensitive display 212, when a touch is detected on touch-sensitive display 212,event comparator 284 performs a hit test to determine which of the three user-interface objects is associated with the touch (sub-event). If each displayed object is associated with arespective event handler 290, the event comparator uses the result of the hit test to determine whichevent handler 290 should be activated. For example,event comparator 284 selects an event handler associated with the sub-event and the object triggering the hit test. - In some embodiments, the definition for a respective event (287) also includes delayed actions that delay delivery of the event information until after it has been determined whether the sequence of sub-events does or does not correspond to the event recognizer's event type.
- When a
respective event recognizer 280 determines that the series of sub-events do not match any of the events inevent definitions 286, therespective event recognizer 280 enters an event impossible, event failed, or event ended state, after which it disregards subsequent sub-events of the touch-based gesture. In this situation, other event recognizers, if any, that remain active for the hit view continue to track and process sub-events of an ongoing touch-based gesture. - In some embodiments, a
respective event recognizer 280 includesmetadata 283 with configurable properties, flags, and/or lists that indicate how the event delivery system should perform sub-event delivery to actively involved event recognizers. In some embodiments,metadata 283 includes configurable properties, flags, and/or lists that indicate how event recognizers may interact, or are enabled to interact, with one another. In some embodiments,metadata 283 includes configurable properties, flags, and/or lists that indicate whether sub-events are delivered to varying levels in the view or programmatic hierarchy. - In some embodiments, a
respective event recognizer 280 activatesevent handler 290 associated with an event when one or more particular sub-events of an event are recognized. In some embodiments, arespective event recognizer 280 delivers event information associated with the event toevent handler 290. Activating anevent handler 290 is distinct from sending (and deferred sending) sub-events to a respective hit view. In some embodiments,event recognizer 280 throws a flag associated with the recognized event, andevent handler 290 associated with the flag catches the flag and performs a predefined process. - In some embodiments,
event delivery instructions 288 include sub-event delivery instructions that deliver event information about a sub-event without activating an event handler. Instead, the sub-event delivery instructions deliver event information to event handlers associated with the series of sub-events or to actively involved views. Event handlers associated with the series of sub-events or with actively involved views receive the event information and perform a predetermined process. - In some embodiments,
data updater 276 creates and updates data used in application 236-1. For example,data updater 276 updates the telephone number used incontacts module 237, or stores a video file used in video player module. In some embodiments, objectupdater 277 creates and updates objects used in application 236-1. For example, objectupdater 277 creates a new user-interface object or updates the position of a user-interface object.GUI updater 278 updates the GUI. For example,GUI updater 278 prepares display information and sends it tographics module 232 for display on a touch-sensitive display. - In some embodiments, event handler(s) 290 includes or has access to
data updater 276,object updater 277, andGUI updater 278. In some embodiments,data updater 276,object updater 277, andGUI updater 278 are included in a single module of a respective application 236-1 orapplication view 291. In other embodiments, they are included in two or more software modules. - It shall be understood that the foregoing discussion regarding event handling of user touches on touch-sensitive displays also applies to other forms of user inputs to operate
multifunction devices 200 with input devices, not all of which are initiated on touch screens. For example, mouse movement and mouse button presses, optionally coordinated with single or multiple keyboard presses or holds; contact movements such as taps, drags, scrolls, etc. on touchpads; pen stylus inputs; movement of the device; oral instructions; detected eye movements; biometric inputs; and/or any combination thereof are optionally utilized as inputs corresponding to sub-events which define an event to be recognized. -
FIG. 3 illustrates aportable multifunction device 200 having atouch screen 212 in accordance with some embodiments. The touch screen optionally displays one or more graphics within user interface (UI) 300. In this embodiment, as well as others described below, a user is enabled to select one or more of the graphics by making a gesture on the graphics, for example, with one or more fingers 302 (not drawn to scale in the figure) or one or more styluses 303 (not drawn to scale in the figure). In some embodiments, selection of one or more graphics occurs when the user breaks contact with the one or more graphics. In some embodiments, the gesture optionally includes one or more taps, one or more swipes (from left to right, right to left, upward and/or downward), and/or a rolling of a finger (from right to left, left to right, upward and/or downward) that has made contact withdevice 200. In some implementations or circumstances, inadvertent contact with a graphic does not select the graphic. For example, a swipe gesture that sweeps over an application icon optionally does not select the corresponding application when the gesture corresponding to selection is a tap. -
Device 200 may also include one or more physical buttons, such as “home” ormenu button 304. As described previously,menu button 304 may be used to navigate to anyapplication 236 in a set of applications that may be executed ondevice 200. Alternatively, in some embodiments, the menu button is implemented as a soft key in a GUI displayed ontouch screen 212. - In one embodiment,
device 200 includestouch screen 212,menu button 304,push button 306 for powering the device on/off and locking the device, volume adjustment button(s) 308, subscriber identity module (SIM)card slot 310,headset jack 312, and docking/chargingexternal port 224.Push button 306 is, optionally, used to turn the power on/off on the device by depressing the button and holding the button in the depressed state for a predefined time interval; to lock the device by depressing the button and releasing the button before the predefined time interval has elapsed; and/or to unlock the device or initiate an unlock process. In an alternative embodiment,device 200 also accepts verbal input for activation or deactivation of some functions throughmicrophone 213.Device 200 also, optionally, includes one or morecontact intensity sensors 265 for detecting intensity of contacts ontouch screen 212 and/or one or moretactile output generators 267 for generating tactile outputs for a user ofdevice 200. -
FIG. 4 is a block diagram of an exemplary multifunction device with a display and a touch-sensitive surface in accordance with some embodiments.Device 400 need not be portable. In some embodiments,device 400 is a laptop computer, a desktop computer, a tablet computer, a multimedia player device, a navigation device, an educational device (such as a child's learning toy), a gaming system, or a control device (e.g., a home or industrial controller).Device 400 typically includes one or more processing units (CPUs) 410, one or more network orother communications interfaces 460,memory 470, and one ormore communication buses 420 for interconnecting these components.Communication buses 420 optionally include circuitry (sometimes called a chipset) that interconnects and controls communications between system components.Device 400 includes input/output (I/O)interface 430 comprisingdisplay 440, which is typically a touch screen display. I/O interface 430 also optionally includes a keyboard and/or mouse (or other pointing device) 450 andtouchpad 455,tactile output generator 457 for generating tactile outputs on device 400 (e.g., similar to tactile output generator(s) 267 described above with reference toFIG. 2A ), sensors 459 (e.g., optical, acceleration, proximity, touch-sensitive, and/or contact intensity sensors similar to contact intensity sensor(s) 265 described above with reference toFIG. 2A ).Memory 470 includes high-speed random access memory, such as DRAM, SRAM, DDR RAM, or other random access solid state memory devices; and optionally includes non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid state storage devices.Memory 470 optionally includes one or more storage devices remotely located from CPU(s) 410. In some embodiments,memory 470 stores programs, modules, and data structures analogous to the programs, modules, and data structures stored inmemory 202 of portable multifunction device 200 (FIG. 2A ), or a subset thereof. Furthermore,memory 470 optionally stores additional programs, modules, and data structures not present inmemory 202 of portablemultifunction device 200. For example,memory 470 ofdevice 400 optionallystores drawing module 480,presentation module 482,word processing module 484,website creation module 486,disk authoring module 488, and/orspreadsheet module 490, whilememory 202 of portable multifunction device 200 (FIG. 2A ) optionally does not store these modules. - Each of the above-identified elements in
FIG. 4 may be stored in one or more of the previously mentioned memory devices. Each of the above-identified modules corresponds to a set of instructions for performing a function described above. The above-identified modules or programs (e.g., sets of instructions) need not be implemented as separate software programs, procedures, or modules, and thus various subsets of these modules may be combined or otherwise rearranged in various embodiments. In some embodiments,memory 470 may store a subset of the modules and data structures identified above. Furthermore,memory 470 may store additional modules and data structures not described above. - Attention is now directed towards embodiments of user interfaces that may be implemented on, for example,
portable multifunction device 200. -
FIG. 5A illustrates an exemplary user interface for a menu of applications onportable multifunction device 200 in accordance with some embodiments. Similar user interfaces may be implemented ondevice 400. In some embodiments,user interface 500 includes the following elements, or a subset or superset thereof: - Signal strength indicator(s) 502 for wireless communication(s), such as cellular and Wi-Fi signals;
-
-
Time 504; -
Bluetooth indicator 505; -
Battery status indicator 506; -
Tray 508 with icons for frequently used applications, such as:-
Icon 516 fortelephone module 238, labeled “Phone,” which optionally includes anindicator 514 of the number of missed calls or voicemail messages; -
Icon 518 fore-mail client module 240, labeled “Mail,” which optionally includes anindicator 510 of the number of unread e-mails; -
Icon 520 forbrowser module 247, labeled “Browser;” and -
Icon 522 for video andmusic player module 252, also referred to as iPod (trademark of Apple Inc.)module 252, labeled “iPod;” and
-
- Icons for other applications, such as:
-
Icon 524 forIM module 241, labeled “Messages;” -
Icon 526 forcalendar module 248, labeled “Calendar;” -
Icon 528 forimage management module 244, labeled “Photos;” -
Icon 530 forcamera module 243, labeled “Camera;” -
Icon 532 foronline video module 255, labeled “Online Video;” -
Icon 534 for stocks widget 249-2, labeled “Stocks;” -
Icon 536 formap module 254, labeled “Maps;” -
Icon 538 for weather widget 249-1, labeled “Weather;” -
Icon 540 for alarm clock widget 249-4, labeled “Clock;” -
Icon 542 forworkout support module 242, labeled “Workout Support;” -
Icon 544 fornotes module 253, labeled “Notes;” and -
Icon 546 for a settings application or module, labeled “Settings,” which provides access to settings fordevice 200 and itsvarious applications 236.
-
-
- It should be noted that the icon labels illustrated in
FIG. 5A are merely exemplary. For example,icon 522 for video andmusic player module 252 may optionally be labeled “Music” or “Music Player.” Other labels are, optionally, used for various application icons. In some embodiments, a label for a respective application icon includes a name of an application corresponding to the respective application icon. In some embodiments, a label for a particular application icon is distinct from a name of an application corresponding to the particular application icon. -
FIG. 5B illustrates an exemplary user interface on a device (e.g.,device 400,FIG. 4 ) with a touch-sensitive surface 551 (e.g., a tablet ortouchpad 455,FIG. 4 ) that is separate from the display 550 (e.g., touch screen display 212).Device 400 also, optionally, includes one or more contact intensity sensors (e.g., one or more of sensors 457) for detecting intensity of contacts on touch-sensitive surface 551 and/or one or moretactile output generators 459 for generating tactile outputs for a user ofdevice 400. - Although some of the examples which follow will be given with reference to inputs on touch screen display 212 (where the touch-sensitive surface and the display are combined), in some embodiments, the device detects inputs on a touch-sensitive surface that is separate from the display, as shown in
FIG. 5B . In some embodiments, the touch-sensitive surface (e.g., 551 inFIG. 5B ) has a primary axis (e.g., 552 inFIG. 5B ) that corresponds to a primary axis (e.g., 553 inFIG. 5B ) on the display (e.g., 550). In accordance with these embodiments, the device detects contacts (e.g., 560 and 562 inFIG. 5B ) with the touch-sensitive surface 551 at locations that correspond to respective locations on the display (e.g., inFIG. 5B, 560 corresponds to 568 and 562 corresponds to 570). In this way, user inputs (e.g.,contacts FIG. 5B ) are used by the device to manipulate the user interface on the display (e.g., 550 inFIG. 5B ) of the multifunction device when the touch-sensitive surface is separate from the display. It should be understood that similar methods are, optionally, used for other user interfaces described herein. - Additionally, while the following examples are given primarily with reference to finger inputs (e.g., finger contacts, finger tap gestures, finger swipe gestures), it should be understood that, in some embodiments, one or more of the finger inputs are replaced with input from another input device (e.g., a mouse-based input or stylus input). For example, a swipe gesture is, optionally, replaced with a mouse click (e.g., instead of a contact) followed by movement of the cursor along the path of the swipe (e.g., instead of movement of the contact). As another example, a tap gesture is, optionally, replaced with a mouse click while the cursor is located over the location of the tap gesture (e.g., instead of detection of the contact followed by ceasing to detect the contact). Similarly, when multiple user inputs are simultaneously detected, it should be understood that multiple computer mice are, optionally, used simultaneously, or a mouse and finger contacts are, optionally, used simultaneously.
-
FIG. 6A illustrates exemplary personalelectronic device 600.Device 600 includesbody 602. In some embodiments,device 600 can include some or all of the features described with respect todevices 200 and 400 (e.g.,FIGS. 2A-4B ). In some embodiments,device 600 has touch-sensitive display screen 604,hereafter touch screen 604. Alternatively, or in addition totouch screen 604,device 600 has a display and a touch-sensitive surface. As withdevices device 600 can respond to touches based on their intensity, meaning that touches of different intensities can invoke different user interface operations ondevice 600. - Techniques for detecting and processing touch intensity may be found, for example, in related applications: International Patent Application Serial No. PCT/US2013/040061, titled “Device, Method, and Graphical User Interface for Displaying User Interface Objects Corresponding to an Application,” filed May 8, 2013, and International Patent Application Serial No. PCT/US2013/069483, titled “Device, Method, and Graphical User Interface for Transitioning Between Touch Input to Display Output Relationships,” filed Nov. 11, 2013, each of which is hereby incorporated by reference in their entirety.
- In some embodiments,
device 600 has one ormore input mechanisms Input mechanisms device 600 has one or more attachment mechanisms. Such attachment mechanisms, if included, can permit attachment ofdevice 600 with, for example, hats, eyewear, earrings, necklaces, shirts, jackets, bracelets, watch straps, chains, trousers, belts, shoes, purses, backpacks, and so forth. These attachment mechanisms may permitdevice 600 to be worn by a user. -
FIG. 6B depicts exemplary personalelectronic device 600. In some embodiments,device 600 can include some or all of the components described with respect toFIGS. 2A, 2B , and 4.Device 600 hasbus 612 that operatively couples I/O section 614 with one ormore computer processors 616 andmemory 618. I/O section 614 can be connected to display 604, which can have touch-sensitive component 622 and, optionally, touch-intensitysensitive component 624. In addition, I/O section 614 can be connected withcommunication unit 630 for receiving application and operating system data, using Wi-Fi, Bluetooth, near field communication (NFC), cellular, and/or other wireless communication techniques.Device 600 can includeinput mechanisms 606 and/or 608.Input mechanism 606 may be a rotatable input device or a depressible and rotatable input device, for example.Input mechanism 608 may be a button, in some examples. -
Input mechanism 608 may be a microphone, in some examples. Personalelectronic device 600 can include various sensors, such asGPS sensor 632,accelerometer 634, directional sensor 640 (e.g., compass),gyroscope 636,motion sensor 638, and/or a combination thereof, all of which can be operatively connected to I/O section 614. -
Memory 618 of personalelectronic device 600 can be a non-transitory computer-readable storage medium, for storing computer-executable instructions, which, when executed by one ormore computer processors 616, for example, can cause the computer processors to perform the techniques described below, including process 900 (FIGS. 8A-D ). The computer-executable instructions can also be stored and/or transported within any non-transitory computer-readable storage medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For purposes of this document, a “non-transitory computer-readable storage medium” can be any medium that can tangibly contain or store computer-executable instructions for use by or in connection with the instruction execution system, apparatus, or device. The non-transitory computer-readable storage medium can include, but is not limited to, magnetic, optical, and/or semiconductor storages. Examples of such storage include magnetic disks, optical discs based on CD, DVD, or Blu-ray technologies, as well as persistent solid-state memory such as flash, solid-state drives, and the like. Personalelectronic device 600 is not limited to the components and configuration ofFIG. 6B , but can include other or additional components in multiple configurations. - As used here, the term “affordance” refers to a user-interactive graphical user interface object that may be displayed on the display screen of
devices FIGS. 2, 4, and 6 ). For example, an image (e.g., icon), a button, and text (e.g., hyperlink) may each constitute an affordance. - As used herein, the term “focus selector” refers to an input element that indicates a current part of a user interface with which a user is interacting. In some implementations that include a cursor or other location marker, the cursor acts as a “focus selector” so that when an input (e.g., a press input) is detected on a touch-sensitive surface (e.g.,
touchpad 455 inFIG. 4 or touch-sensitive surface 551 inFIG. 5B ) while the cursor is over a particular user interface element (e.g., a button, window, slider or other user interface element), the particular user interface element is adjusted in accordance with the detected input. In some implementations that include a touch screen display (e.g., touch-sensitive display system 212 inFIG. 2A ortouch screen 212 inFIG. 5A ) that enables direct interaction with user interface elements on the touch screen display, a detected contact on the touch screen acts as a “focus selector” so that when an input (e.g., a press input by the contact) is detected on the touch screen display at a location of a particular user interface element (e.g., a button, window, slider, or other user interface element), the particular user interface element is adjusted in accordance with the detected input. In some implementations, focus is moved from one region of a user interface to another region of the user interface without corresponding movement of a cursor or movement of a contact on a touch screen display (e.g., by using a tab key or arrow keys to move focus from one button to another button); in these implementations, the focus selector moves in accordance with movement of focus between different regions of the user interface. Without regard to the specific form taken by the focus selector, the focus selector is generally the user interface element (or contact on a touch screen display) that is controlled by the user so as to communicate the user's intended interaction with the user interface (e.g., by indicating, to the device, the element of the user interface with which the user is intending to interact). For example, the location of a focus selector (e.g., a cursor, a contact, or a selection box) over a respective button while a press input is detected on the touch-sensitive surface (e.g., a touchpad or touch screen) will indicate that the user is intending to activate the respective button (as opposed to other user interface elements shown on a display of the device). - As used in the specification and claims, the term “characteristic intensity” of a contact refers to a characteristic of the contact based on one or more intensities of the contact. In some embodiments, the characteristic intensity is based on multiple intensity samples. The characteristic intensity is, optionally, based on a predefined number of intensity samples, or a set of intensity samples collected during a predetermined time period (e.g., 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10 seconds) relative to a predefined event (e.g., after detecting the contact, prior to detecting liftoff of the contact, before or after detecting a start of movement of the contact, prior to detecting an end of the contact, before or after detecting an increase in intensity of the contact, and/or before or after detecting a decrease in intensity of the contact). A characteristic intensity of a contact is, optionally based on one or more of: a maximum value of the intensities of the contact, a mean value of the intensities of the contact, an average value of the intensities of the contact, a top 10 percentile value of the intensities of the contact, a value at the half maximum of the intensities of the contact, a value at the 90 percent maximum of the intensities of the contact, or the like. In some embodiments, the duration of the contact is used in determining the characteristic intensity (e.g., when the characteristic intensity is an average of the intensity of the contact over time). In some embodiments, the characteristic intensity is compared to a set of one or more intensity thresholds to determine whether an operation has been performed by a user. For example, the set of one or more intensity thresholds may include a first intensity threshold and a second intensity threshold. In this example, a contact with a characteristic intensity that does not exceed the first threshold results in a first operation, a contact with a characteristic intensity that exceeds the first intensity threshold and does not exceed the second intensity threshold results in a second operation, and a contact with a characteristic intensity that exceeds the second threshold results in a third operation. In some embodiments, a comparison between the characteristic intensity and one or more thresholds is used to determine whether or not to perform one or more operations (e.g., whether to perform a respective operation or forgo performing the respective operation) rather than being used to determine whether to perform a first operation or a second operation.
- In some embodiments, a portion of a gesture is identified for purposes of determining a characteristic intensity. For example, a touch-sensitive surface may receive a continuous swipe contact transitioning from a start location and reaching an end location, at which point the intensity of the contact increases. In this example, the characteristic intensity of the contact at the end location may be based on only a portion of the continuous swipe contact, and not the entire swipe contact (e.g., only the portion of the swipe contact at the end location). In some embodiments, a smoothing algorithm may be applied to the intensities of the swipe contact prior to determining the characteristic intensity of the contact. For example, the smoothing algorithm optionally includes one or more of: an unweighted sliding-average smoothing algorithm, a triangular smoothing algorithm, a median filter smoothing algorithm, and/or an exponential smoothing algorithm. In some circumstances, these smoothing algorithms eliminate narrow spikes or dips in the intensities of the swipe contact for purposes of determining a characteristic intensity.
- The intensity of a contact on the touch-sensitive surface may be characterized relative to one or more intensity thresholds, such as a contact-detection intensity threshold, a light press intensity threshold, a deep press intensity threshold, and/or one or more other intensity thresholds. In some embodiments, the light press intensity threshold corresponds to an intensity at which the device will perform operations typically associated with clicking a button of a physical mouse or a trackpad. In some embodiments, the deep press intensity threshold corresponds to an intensity at which the device will perform operations that are different from operations typically associated with clicking a button of a physical mouse or a trackpad. In some embodiments, when a contact is detected with a characteristic intensity below the light press intensity threshold (e.g., and above a nominal contact-detection intensity threshold below which the contact is no longer detected), the device will move a focus selector in accordance with movement of the contact on the touch-sensitive surface without performing an operation associated with the light press intensity threshold or the deep press intensity threshold. Generally, unless otherwise stated, these intensity thresholds are consistent between different sets of user interface figures.
- An increase of characteristic intensity of the contact from an intensity below the light press intensity threshold to an intensity between the light press intensity threshold and the deep press intensity threshold is sometimes referred to as a “light press” input. An increase of characteristic intensity of the contact from an intensity below the deep press intensity threshold to an intensity above the deep press intensity threshold is sometimes referred to as a “deep press” input. An increase of characteristic intensity of the contact from an intensity below the contact-detection intensity threshold to an intensity between the contact-detection intensity threshold and the light press intensity threshold is sometimes referred to as detecting the contact on the touch-surface. A decrease of characteristic intensity of the contact from an intensity above the contact-detection intensity threshold to an intensity below the contact-detection intensity threshold is sometimes referred to as detecting liftoff of the contact from the touch-surface. In some embodiments, the contact-detection intensity threshold is zero. In some embodiments, the contact-detection intensity threshold is greater than zero.
- In some embodiments described herein, one or more operations are performed in response to detecting a gesture that includes a respective press input or in response to detecting the respective press input performed with a respective contact (or a plurality of contacts), where the respective press input is detected based at least in part on detecting an increase in intensity of the contact (or plurality of contacts) above a press-input intensity threshold. In some embodiments, the respective operation is performed in response to detecting the increase in intensity of the respective contact above the press-input intensity threshold (e.g., a “down stroke” of the respective press input). In some embodiments, the press input includes an increase in intensity of the respective contact above the press-input intensity threshold and a subsequent decrease in intensity of the contact below the press-input intensity threshold, and the respective operation is performed in response to detecting the subsequent decrease in intensity of the respective contact below the press-input threshold (e.g., an “up stroke” of the respective press input).
- In some embodiments, the device employs intensity hysteresis to avoid accidental inputs sometimes termed “jitter,” where the device defines or selects a hysteresis intensity threshold with a predefined relationship to the press-input intensity threshold (e.g., the hysteresis intensity threshold is X intensity units lower than the press-input intensity threshold or the hysteresis intensity threshold is 75%, 90%, or some reasonable proportion of the press-input intensity threshold). Thus, in some embodiments, the press input includes an increase in intensity of the respective contact above the press-input intensity threshold and a subsequent decrease in intensity of the contact below the hysteresis intensity threshold that corresponds to the press-input intensity threshold, and the respective operation is performed in response to detecting the subsequent decrease in intensity of the respective contact below the hysteresis intensity threshold (e.g., an “up stroke” of the respective press input). Similarly, in some embodiments, the press input is detected only when the device detects an increase in intensity of the contact from an intensity at or below the hysteresis intensity threshold to an intensity at or above the press-input intensity threshold and, optionally, a subsequent decrease in intensity of the contact to an intensity at or below the hysteresis intensity, and the respective operation is performed in response to detecting the press input (e.g., the increase in intensity of the contact or the decrease in intensity of the contact, depending on the circumstances).
- For ease of explanation, the descriptions of operations performed in response to a press input associated with a press-input intensity threshold or in response to a gesture including the press input are, optionally, triggered in response to detecting either: an increase in intensity of a contact above the press-input intensity threshold, an increase in intensity of a contact from an intensity below the hysteresis intensity threshold to an intensity above the press-input intensity threshold, a decrease in intensity of the contact below the press-input intensity threshold, and/or a decrease in intensity of the contact below the hysteresis intensity threshold corresponding to the press-input intensity threshold. Additionally, in examples where an operation is described as being performed in response to detecting a decrease in intensity of a contact below the press-input intensity threshold, the operation is, optionally, performed in response to detecting a decrease in intensity of the contact below a hysteresis intensity threshold corresponding to, and lower than, the press-input intensity threshold.
-
FIG. 7A illustrates a block diagram ofdigital assistant system 700 in accordance with various examples. In some examples,digital assistant system 700 can be implemented on a standalone computer system. In some examples,digital assistant system 700 can be distributed across multiple computers. In some examples, some of the modules and functions of the digital assistant can be divided into a server portion and a client portion, where the client portion resides on one or more user devices (e.g.,devices FIG. 1 . In some examples,digital assistant system 700 can be an implementation of server system 108 (and/or DA server 106) shown inFIG. 1 . It should be noted thatdigital assistant system 700 is only one example of a digital assistant system, and thatdigital assistant system 700 can have more or fewer components than shown, may combine two or more components, or may have a different configuration or arrangement of the components. The various components shown inFIG. 7A can be implemented in hardware, software instructions for execution by one or more processors, firmware, including one or more signal processing and/or application specific integrated circuits, or a combination thereof. -
Digital assistant system 700 can includememory 702, one ormore processors 704, input/output (I/O)interface 706, andnetwork communications interface 708. These components can communicate with one another over one or more communication buses or signal lines 710. - In some examples,
memory 702 can include a non-transitory computer-readable medium, such as high-speed random access memory and/or a non-volatile computer-readable storage medium (e.g., one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices). - In some examples, I/
O interface 706 can couple input/output devices 716 ofdigital assistant system 700, such as displays, keyboards, touch screens, and microphones, touser interface module 722. I/O interface 706, in conjunction withuser interface module 722, can receive user inputs (e.g., voice input, keyboard inputs, touch inputs, etc.) and processes them accordingly. In some examples, e.g., when the digital assistant is implemented on a standalone user device,digital assistant system 700 can include any of the components and I/O communication interfaces described with respect todevices FIGS. 2A, 4, 6A -B, respectively. In some examples,digital assistant system 700 can represent the server portion of a digital assistant implementation, and can interact with the user through a client-side portion residing on a user device (e.g.,devices - In some examples, the
network communications interface 708 can include wired communication port(s) 712 and/or wireless transmission andreception circuitry 714. The wired communication port(s) can receive and send communication signals via one or more wired interfaces, e.g., Ethernet, Universal Serial Bus (USB), FIREWIRE, etc. Thewireless circuitry 714 can receive and send RF signals and/or optical signals from/to communications networks and other communications devices. The wireless communications can use any of a plurality of communications standards, protocols, and technologies, such as GSM, EDGE, CDMA, TDMA, Bluetooth, Wi-Fi, VoIP, Wi-MAX, or any other suitable communication protocol. Network communications interface 708 can enable communication between digitalassistant system 700 with networks, such as the Internet, an intranet, and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN), and/or a metropolitan area network (MAN), and other devices. - In some examples,
memory 702, or the computer-readable storage media ofmemory 702, can store programs, modules, instructions, and data structures including all or a subset of: operatingsystem 718,communications module 720,user interface module 722, one ormore applications 724, anddigital assistant module 726. In particular,memory 702, or the computer-readable storage media ofmemory 702, can store instructions for performingprocess 900, described below. One ormore processors 704 can execute these programs, modules, and instructions, and reads/writes from/to the data structures. - Operating system 718 (e.g., Darwin, RTXC, LINUX, UNIX, iOS, OS X, WINDOWS, or an embedded operating system such as VxWorks) can include various software components and/or drivers for controlling and managing general system tasks (e.g., memory management, storage device control, power management, etc.) and facilitates communications between various hardware, firmware, and software components.
-
Communications module 720 can facilitate communications between digitalassistant system 700 with other devices overnetwork communications interface 708. For example,communications module 720 can communicate withRF circuitry 208 of electronic devices such asdevices FIG. 2A, 4, 6A -B, respectively.Communications module 720 can also include various components for handling data received bywireless circuitry 714 and/or wiredcommunications port 712. -
User interface module 722 can receive commands and/or inputs from a user via I/O interface 706 (e.g., from a keyboard, touch screen, pointing device, controller, and/or microphone), and generate user interface objects on a display.User interface module 722 can also prepare and deliver outputs (e.g., speech, sound, animation, text, icons, vibrations, haptic feedback, light, etc.) to the user via the I/O interface 706 (e.g., through displays, audio channels, speakers, touch-pads, etc.). -
Applications 724 can include programs and/or modules that are configured to be executed by one ormore processors 704. For example, if the digital assistant system is implemented on a standalone user device,applications 724 can include user applications, such as games, a calendar application, a navigation application, or an email application. Ifdigital assistant system 700 is implemented on a server,applications 724 can include resource management applications, diagnostic applications, or scheduling applications, for example. -
Memory 702 can also store digital assistant module 726 (or the server portion of a digital assistant). In some examples,digital assistant module 726 can include the following sub-modules, or a subset or superset thereof: input/output processing module 728, speech-to-text (STT)processing module 730, naturallanguage processing module 732, dialogueflow processing module 734, taskflow processing module 736,service processing module 738, andspeech synthesis module 740. Each of these modules can have access to one or more of the following systems or data and models of thedigital assistant module 726, or a subset or superset thereof:ontology 760,vocabulary index 744,user data 748,task flow models 754,service models 756, and ASR systems. - In some examples, using the processing modules, data, and models implemented in
digital assistant module 726, the digital assistant can perform at least some of the following: converting speech input into text; identifying a user's intent expressed in a natural language input received from the user; actively eliciting and obtaining information needed to fully infer the user's intent (e.g., by disambiguating words, games, intentions, etc.); determining the task flow for fulfilling the inferred intent; and executing the task flow to fulfill the inferred intent. - In some examples, as shown in
FIG. 7B , I/O processing module 728 can interact with the user through I/O devices 716 inFIG. 7A or with a user device (e.g.,devices network communications interface 708 inFIG. 7A to obtain user input (e.g., a speech input) and to provide responses (e.g., as speech outputs) to the user input. I/O processing module 728 can optionally obtain contextual information associated with the user input from the user device, along with or shortly after the receipt of the user input. The contextual information can include user-specific data, vocabulary, and/or preferences relevant to the user input. In some examples, the contextual information also includes software and hardware states of the user device at the time the user request is received, and/or information related to the surrounding environment of the user at the time that the user request was received. In some examples, I/O processing module 728 can also send follow-up questions to, and receive answers from, the user regarding the user request. When a user request is received by I/O processing module 728 and the user request can include speech input, I/O processing module 728 can forward the speech input to STT processing module 730 (or speech recognizer) for speech-to-text conversions. -
STT processing module 730 can include one or more ASR systems. The one or more ASR systems can process the speech input that is received through I/O processing module 728 to produce a recognition result. Each ASR system can include a front-end speech pre-processor. The front-end speech pre-processor can extract representative features from the speech input. For example, the front-end speech pre-processor can perform a Fourier transform on the speech input to extract spectral features that characterize the speech input as a sequence of representative multi-dimensional vectors. Further, each ASR system can include one or more speech recognition models (e.g., acoustic models and/or language models) and can implement one or more speech recognition engines. Examples of speech recognition models can include Hidden Markov Models, Gaussian-Mixture Models, Deep Neural Network Models, n-gram language models, and other statistical models. Examples of speech recognition engines can include the dynamic time warping based engines and weighted finite-state transducers (WFST) based engines. The one or more speech recognition models and the one or more speech recognition engines can be used to process the extracted representative features of the front-end speech pre-processor to produce intermediate recognitions results (e.g., phonemes, phonemic strings, and sub-words), and ultimately, text recognition results (e.g., words, word strings, or sequence of tokens). In some examples, the speech input can be processed at least partially by a third-party service or on the user's device (e.g.,device STT processing module 730 produces recognition results containing a text string (e.g., words, or sequence of words, or sequence of tokens), the recognition result can be passed to naturallanguage processing module 732 for intent deduction. - More details on the speech-to-text processing are described in U.S. Utility application Ser. No. 13/236,942 for “Consolidating Speech Recognition Results,” filed on Sep. 20, 2011, the entire disclosure of which is incorporated herein by reference.
- In some examples,
STT processing module 730 can include and/or access a vocabulary of recognizable words via phoneticalphabet conversion module 731. Each vocabulary word can be associated with one or more candidate pronunciations of the word represented in a speech recognition phonetic alphabet. In particular, the vocabulary of recognizable words can include a word that is associated with a plurality of candidate pronunciations. For example, the vocabulary may include the word “tomato” that is associated with the candidate pronunciations of // and //. Further, vocabulary words can be associated with custom candidate pronunciations that are based on previous speech inputs from the user. Such custom candidate pronunciations can be stored inSTT processing module 730 and can be associated with a particular user via the user's profile on the device. In some examples, the candidate pronunciations for words can be determined based on the spelling of the word and one or more linguistic and/or phonetic rules. In some examples, the candidate pronunciations can be manually generated, e.g., based on known canonical pronunciations. - In some examples, the candidate pronunciations can be ranked based on the commonness of the candidate pronunciation. For example, the candidate pronunciation // can be ranked higher than //, because the former is a more commonly used pronunciation (e.g., among all users, for users in a particular geographical region, or for any other appropriate subset of users). In some examples, candidate pronunciations can be ranked based on whether the candidate pronunciation is a custom candidate pronunciation associated with the user. For example, custom candidate pronunciations can be ranked higher than canonical candidate pronunciations. This can be useful for recognizing proper nouns having a unique pronunciation that deviates from canonical pronunciation. In some examples, candidate pronunciations can be associated with one or more speech characteristics, such as geographic origin, nationality, or ethnicity. For example, the candidate pronunciation // can be associated with the United States, whereas the candidate pronunciation // can be associated with Great Britain. Further, the rank of the candidate pronunciation can be based on one or more characteristics (e.g., geographic origin, nationality, ethnicity, etc.) of the user stored in the user's profile on the device. For example, it can be determined from the user's profile that the user is associated with the United States. Based on the user being associated with the United States, the candidate pronunciation // (associated with the United States) can be ranked higher than the candidate pronunciation // (associated with Great Britain). In some examples, one of the ranked candidate pronunciations can be selected as a predicted pronunciation (e.g., the most likely pronunciation).
- When a speech input is received,
STT processing module 730 can be used to determine the phonemes corresponding to the speech input (e.g., using an acoustic model), and then attempt to determine words that match the phonemes (e.g., using a language model). For example, ifSTT processing module 730 can first identify the sequence of phonemes // corresponding to a portion of the speech input, it can then determine, based onvocabulary index 744, that this sequence corresponds to the word “tomato.” - In some examples,
STT processing module 730 can use approximate matching techniques to determine words in an utterance. Thus, for example, theSTT processing module 730 can determine that the sequence of phonemes // corresponds to the word “tomato,” even if that particular sequence of phonemes is not one of the candidate sequence of phonemes for that word. - In some examples, natural
language processing module 732 can be configured to receive metadata associated with the speech input. The metadata can indicate whether to perform natural language processing on the speech input (or the sequence of words or tokens corresponding to the speech input). If the metadata indicates that natural language processing is to be performed, then the natural language processing module can receive the sequence of words or tokens from the STT processing module to perform natural language processing. However, if the metadata indicates that natural language process is not to be performed, then the natural language processing module can be disabled and the sequence of words or tokens (e.g., text string) from the STT processing module can be outputted from the digital assistant. In some examples, the metadata can further identify one or more domains corresponding to the user request. Based on the one or more domains, the natural language processor can disable domains inontology 760 other than the one or more domains. In this way, natural language processing is constrained to the one or more domains inontology 760. In particular, the structure query (described below) can be generated using the one or more domains and not the other domains in the ontology. - Natural language processing module 732 (“natural language processor”) of the digital assistant can take the sequence of words or tokens (“token sequence”) generated by
STT processing module 730, and attempt to associate the token sequence with one or more “actionable intents” recognized by the digital assistant. An “actionable intent” can represent a task that can be performed by the digital assistant, and can have an associated task flow implemented intask flow models 754. The associated task flow can be a series of programmed actions and steps that the digital assistant takes in order to perform the task. The scope of a digital assistant's capabilities can be dependent on the number and variety of task flows that have been implemented and stored intask flow models 754, or in other words, on the number and variety of “actionable intents” that the digital assistant recognizes. The effectiveness of the digital assistant, however, can also be dependent on the assistant's ability to infer the correct “actionable intent(s)” from the user request expressed in natural language. - In some examples, in addition to the sequence of words or tokens obtained from
STT processing module 730, naturallanguage processing module 732 can also receive contextual information associated with the user request, e.g., from I/O processing module 728. The naturallanguage processing module 732 can optionally use the contextual information to clarify, supplement, and/or further define the information contained in the token sequence received fromSTT processing module 730. The contextual information can include, for example, user preferences, hardware, and/or software states of the user device, sensor information collected before, during, or shortly after the user request, prior interactions (e.g., dialogue) between the digital assistant and the user, and the like. As described herein, contextual information can be dynamic, and can change with time, location, content of the dialogue, and other factors. - In some examples, the natural language processing can be based on, e.g.,
ontology 760.Ontology 760 can be a hierarchical structure containing many nodes, each node representing either an “actionable intent” or a “property” relevant to one or more of the “actionable intents” or other “properties.” As noted above, an “actionable intent” can represent a task that the digital assistant is capable of performing, i.e., it is “actionable” or can be acted on. A “property” can represent a parameter associated with an actionable intent or a sub-aspect of another property. A linkage between an actionable intent node and a property node inontology 760 can define how a parameter represented by the property node pertains to the task represented by the actionable intent node. - In some examples,
ontology 760 can be made up of actionable intent nodes and property nodes. Withinontology 760, each actionable intent node can be linked to one or more property nodes either directly or through one or more intermediate property nodes. Similarly, each property node can be linked to one or more actionable intent nodes either directly or through one or more intermediate property nodes. For example, as shown inFIG. 7C ,ontology 760 can include a “restaurant reservation” node (i.e., an actionable intent node). Property nodes “restaurant,” “date/time” (for the reservation), and “party size” can each be directly linked to the actionable intent node (i.e., the “restaurant reservation” node). - In addition, property nodes “cuisine,” “price range,” “phone number,” and “location” can be sub-nodes of the property node “restaurant,” and can each be linked to the “restaurant reservation” node (i.e., the actionable intent node) through the intermediate property node “restaurant.” For another example, as shown in
FIG. 7C ,ontology 760 can also include a “set reminder” node (i.e., another actionable intent node). Property nodes “date/time” (for setting the reminder) and “subject” (for the reminder) can each be linked to the “set reminder” node. Since the property “date/time” can be relevant to both the task of making a restaurant reservation and the task of setting a reminder, the property node “date/time” can be linked to both the “restaurant reservation” node and the “set reminder” node inontology 760. - An actionable intent node, along with its linked concept nodes, can be described as a “domain.” In the present discussion, each domain can be associated with a respective actionable intent, and refers to the group of nodes (and the relationships there between) associated with the particular actionable intent. For example,
ontology 760 shown inFIG. 7C can include an example ofrestaurant reservation domain 762 and an example ofreminder domain 764 withinontology 760. The restaurant reservation domain includes the actionable intent node “restaurant reservation,” property nodes “restaurant,” “date/time,” and “party size,” and sub-property nodes “cuisine,” “price range,” “phone number,” and “location.”Reminder domain 764 can include the actionable intent node “set reminder,” and property nodes “subject” and “date/time.” In some examples,ontology 760 can be made up of many domains. Each domain can share one or more property nodes with one or more other domains. For example, the “date/time” property node can be associated with many different domains (e.g., a scheduling domain, a travel reservation domain, a movie ticket domain, etc.), in addition torestaurant reservation domain 762 andreminder domain 764. - While
FIG. 7C illustrates two example domains withinontology 760, other domains can include, for example, “find a movie,” “initiate a phone call,” “find directions,” “schedule a meeting,” “send a message,” and “provide an answer to a question,” “read a list,” “providing navigation instructions,” “provide instructions for a task” and so on. A “send a message” domain can be associated with a “send a message” actionable intent node, and may further include property nodes such as “recipient(s),” “message type,” and “message body.” The property node “recipient” can be further defined, for example, by the sub-property nodes such as “recipient name” and “message address.” - In some examples,
ontology 760 can include all the domains (and hence actionable intents) that the digital assistant is capable of understanding and acting upon. In some examples,ontology 760 can be modified, such as by adding or removing entire domains or nodes, or by modifying relationships between the nodes within theontology 760. - In some examples, nodes associated with multiple related actionable intents can be clustered under a “super domain” in
ontology 760. For example, a “travel” super-domain can include a cluster of property nodes and actionable intent nodes related to travel. The actionable intent nodes related to travel can include “airline reservation,” “hotel reservation,” “car rental,” “get directions,” “find points of interest,” and so on. The actionable intent nodes under the same super domain (e.g., the “travel” super domain) can have many property nodes in common. For example, the actionable intent nodes for “airline reservation,” “hotel reservation,” “car rental,” “get directions,” and “find points of interest” can share one or more of the property nodes “start location,” “destination,” “departure date/time,” “arrival date/time,” and “party size.” - In some examples, each node in
ontology 760 can be associated with a set of words and/or phrases that are relevant to the property or actionable intent represented by the node. The respective set of words and/or phrases associated with each node can be the so-called “vocabulary” associated with the node. The respective set of words and/or phrases associated with each node can be stored invocabulary index 744 in association with the property or actionable intent represented by the node. For example, returning toFIG. 7B , the vocabulary associated with the node for the property of “restaurant” can include words such as “food,” “drinks,” “cuisine,” “hungry,” “eat,” “pizza,” “fast food,” “meal,” and so on. For another example, the vocabulary associated with the node for the actionable intent of “initiate a phone call” can include words and phrases such as “call,” “phone,” “dial,” “ring,” “call this number,” “make a call to,” and so on. Thevocabulary index 744 can optionally include words and phrases in different languages. - Natural
language processing module 732 can receive the token sequence (e.g., a text string) fromSTT processing module 730, and determine what nodes are implicated by the words in the token sequence. In some examples, if a word or phrase in the token sequence is found to be associated with one or more nodes in ontology 760 (via vocabulary index 744), the word or phrase can “trigger” or “activate” those nodes. Based on the quantity and/or relative importance of the activated nodes, naturallanguage processing module 732 can select one of the actionable intents as the task that the user intended the digital assistant to perform. In some examples, the domain that has the most “triggered” nodes can be selected. In some examples, the domain having the highest confidence value (e.g., based on the relative importance of its various triggered nodes) can be selected. In some examples, the domain can be selected based on a combination of the number and the importance of the triggered nodes. In some examples, additional factors are considered in selecting the node as well, such as whether the digital assistant has previously correctly interpreted a similar request from a user. -
User data 748 can include user-specific information, such as user-specific vocabulary, user preferences, user address, user's default and secondary languages, user's contact list, and other short-term or long-term information for each user. In some examples, naturallanguage processing module 732 can use the user-specific information to supplement the information contained in the user input to further define the user intent. For example, for a user request “invite my friends to my birthday party,” naturallanguage processing module 732 can be able to accessuser data 748 to determine who the “friends” are and when and where the “birthday party” would be held, rather than requiring the user to provide such information explicitly in his/her request. - Other details of searching an ontology based on a token string is described in U.S. Utility application Ser. No. 12/341,743 for “Method and Apparatus for Searching Using An Active Ontology,” filed Dec. 22, 2008, the entire disclosure of which is incorporated herein by reference.
- In some examples, once natural
language processing module 732 identifies an actionable intent (or domain) based on the user request, naturallanguage processing module 732 can generate a structured query to represent the identified actionable intent. In some examples, the structured query can include parameters for one or more nodes within the domain for the actionable intent, and at least some of the parameters are populated with the specific information and requirements specified in the user request. For example, the user may say “Make me a dinner reservation at a sushi place at 7.” In this case, naturallanguage processing module 732 can be able to correctly identify the actionable intent to be “restaurant reservation” based on the user input. According to the ontology, a structured query for a “restaurant reservation” domain may include parameters such as {Cuisine}, {Time}, {Date}, {Party Size}, and the like. In some examples, based on the speech input and the text derived from the speech input usingSTT processing module 730, naturallanguage processing module 732 can generate a partial structured query for the restaurant reservation domain, where the partial structured query includes the parameters {Cuisine=“Sushi”} and {Time=“7 pm”}. However, in this example, the user's utterance contains insufficient information to complete the structured query associated with the domain. Therefore, other necessary parameters such as {Party Size} and {Date} may not be specified in the structured query based on the information currently available. In some examples, naturallanguage processing module 732 can populate some parameters of the structured query with received contextual information. For example, in some examples, if the user requested a sushi restaurant “near me,” naturallanguage processing module 732 can populate a {location} parameter in the structured query with GPS coordinates from the user device. - In some examples, natural
language processing module 732 can pass the generated structured query (including any completed parameters) to task flow processing module 736 (“task flow processor”). Taskflow processing module 736 can be configured to receive the structured query from naturallanguage processing module 732, complete the structured query, if necessary, and perform the actions required to “complete” the user's ultimate request. In some examples, the various procedures necessary to complete these tasks can be provided intask flow models 754. In some examples,task flow models 754 can include procedures for obtaining additional information from the user and task flows for performing actions associated with the actionable intent. - As described above, in order to complete a structured query, task
flow processing module 736 may need to initiate additional dialogue with the user in order to obtain additional information, and/or disambiguate potentially ambiguous utterances. When such interactions are necessary, taskflow processing module 736 can invoke dialogueflow processing module 734 to engage in a dialogue with the user. In some examples, dialogueflow processing module 734 can determine how (and/or when) to ask the user for the additional information and receives and processes the user responses. The questions can be provided to and answers can be received from the users through I/O processing module 728. In some examples, dialogueflow processing module 734 can present dialogue output to the user via audio and/or visual output, and receives input from the user via spoken or physical (e.g., clicking) responses. Continuing with the example above, when taskflow processing module 736 invokes dialogueflow processing module 734 to determine the “party size” and “date” information for the structured query associated with the domain “restaurant reservation,” dialogueflow processing module 734 can generate questions such as “For how many people?” and “On which day?” to pass to the user. Once answers are received from the user, dialogueflow processing module 734 can then populate the structured query with the missing information, or pass the information to taskflow processing module 736 to complete the missing information from the structured query. - Once task
flow processing module 736 has completed the structured query for an actionable intent, taskflow processing module 736 can proceed to perform the ultimate task associated with the actionable intent. Accordingly, taskflow processing module 736 can execute the steps and instructions in the task flow model according to the specific parameters contained in the structured query. For example, the task flow model for the actionable intent of “restaurant reservation” can include steps and instructions for contacting a restaurant and actually requesting a reservation for a particular party size at a particular time. For example, using a structured query such as: {restaurant reservation, restaurant=ABC Café, date=3/12/2012, time=7 pm, party size=5}, taskflow processing module 736 can perform the steps of: (1) logging onto a server of the ABC Café or a restaurant reservation system such as OPENTABLE®, (2) entering the date, time, and party size information in a form on the website, (3) submitting the form, and (4) making a calendar entry for the reservation in the user's calendar. - In some examples, task
flow processing module 736 can employ the assistance of service processing module 738 (“service processing module”) to complete a task requested in the user input or to provide an informational answer requested in the user input. For example,service processing module 738 can act on behalf of taskflow processing module 736 to make a phone call, set a calendar entry, invoke a map search, invoke or interact with other user applications installed on the user device, and invoke or interact with third-party services (e.g., a restaurant reservation portal, a social networking website, a banking portal, etc.). In some examples, the protocols and application programming interfaces (API) required by each service can be specified by a respective service model amongservice models 756.Service processing module 738 can access the appropriate service model for a service and generate requests for the service in accordance with the protocols and APIs required by the service according to the service model. - For example, if a restaurant has enabled an online reservation service, the restaurant can submit a service model specifying the necessary parameters for making a reservation and the APIs for communicating the values of the necessary parameter to the online reservation service. When requested by task
flow processing module 736,service processing module 738 can establish a network connection with the online reservation service using the web address stored in the service model, and send the necessary parameters of the reservation (e.g., time, date, party size) to the online reservation interface in a format according to the API of the online reservation service. - In some examples, natural
language processing module 732, dialogueflow processing module 734, and taskflow processing module 736 can be used collectively and iteratively to infer and define the user's intent, obtain information to further clarify and refine the user intent, and finally generate a response (i.e., an output to the user, or the completion of a task) to fulfill the user's intent. The generated response can be a dialogue response to the speech input that at least partially fulfills the user's intent. Further, in some examples, the generated response can be output as a speech output. In these examples, the generated response can be sent to speech synthesis module 740 (e.g., speech synthesizer) where it can be processed to synthesize the dialogue response in speech form. In yet other examples, the generated response can be data content relevant to satisfying a user request in the speech input. -
Speech synthesis module 740 can be configured to synthesize speech outputs for presentation to the user.Speech synthesis module 740 synthesizes speech outputs based on text provided by the digital assistant. For example, the generated dialogue response can be in the form of a text string.Speech synthesis module 740 can convert the text string to an audible speech output.Speech synthesis module 740 can use any appropriate speech synthesis technique in order to generate speech outputs from text, including, but not limited, to concatenative synthesis, unit selection synthesis, diphone synthesis, domain-specific synthesis, formant synthesis, articulatory synthesis, hidden Markov model (HMM) based synthesis, and sinewave synthesis. In some examples,speech synthesis module 740 can be configured to synthesize individual words based on phonemic strings corresponding to the words. For example, a phonemic string can be associated with a word in the generated dialogue response. The phonemic string can be stored in metadata associated with the word.Speech synthesis model 740 can be configured to directly process the phonemic string in the metadata to synthesize the word in speech form. - In some examples, instead of (or in addition to) using
speech synthesis module 740, speech synthesis can be performed on a remote device (e.g., the server system 108), and the synthesized speech can be sent to the user device for output to the user. For example, this can occur in some implementations where outputs for a digital assistant are generated at a server system. And because server systems generally have more processing power or resources than a user device, it can be possible to obtain higher quality speech outputs than would be practical with client-side synthesis. - Additional details on digital assistants can be found in the U.S. Utility application Ser. No. 12/987,982, entitled “Intelligent Automated Assistant,” filed Jan. 10, 2011, and U.S. Utility application Ser. No. 13/251,088, entitled “Generating and Processing Task Items That Represent Tasks to Perform,” filed Sep. 30, 2011, the entire disclosures of which are incorporated herein by reference.
-
FIGS. 8A-8Q illustrate exemplary user interfaces for discovering media based on a nonspecific, unstructured natural language request, in accordance with some embodiments. The user interfaces in these figures are used to illustrate the processes described below, including the exemplary processes inFIGS. 9A-9C . - Referring to
FIG. 8A , anelectronic device 200 includes adisplay 212 and amicrophone 213 in accordance with some embodiments. A digital assistant, as described above is, accessed by a user, who utters unstructured natural language user input that is acquired via themicrophone 213. The timing of the user request is under the control of the user. The user can request the delivery of media during the concurrent playback of other media by theelectronic device 200, or while theelectronic device 200 is not playing back media. The user input requests the delivery of particular media, in this case a song. The user input is converted from speech to text, and in accordance with some embodiments, thetextual user input 1000 is displayed on thedisplay 212. By displaying thetextual user input 1000, in accordance with some embodiments, the user can verify that the digital assistant has received correctly the request as made. In other embodiments, such as but not limited to embodiments in which the digital assistant is operable in a hands-free mode, thetextual user input 1000 is not displayed. As illustrated inFIG. 8A , the user has requested the digital assistant to play a specific track from an album entitled “Liszt: The Piano Concertos.” At least part of the album is stored in electronic form on theelectronic device 200, in some embodiments. In other embodiments, at least part of the album is stored remotely (in the “cloud”) on an external device accessible to theelectronic device 200. The remotely stored content is associated with theelectronic device 200 and/or a unique identifier associated with the user, in accordance with some embodiments. In other embodiments, at least part of the album is part of a streaming service, such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.), that is accessible to theelectronic device 200. - Upon receiving unstructured natural language user input requesting media, the digital assistant causes a search for that media to be performed, as described in greater detail with regard to
FIGS. 9A-9C . That search is performed utilizing the unstructured natural language user input, and the context of that input. In this example, the search finds the specific media requested by the user,track 2 of “Liszt: The Piano Concertos,” determining based on the user input and its context that the specific album satisfies the user request. In some embodiments, it is transparent to the user whether the media requested by the user is locally present on theelectronic device 200, stored remotely on a server, or streamed to the user by a streaming service such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). As illustrated inFIG. 8B , the digital assistant obtains the requested media. Theelectronic device 200 presents anidentifier 1002 associated with the media on thedisplay 212, in accordance with some embodiments, to allow the user to confirm which media is being played back. Theelectronic device 200 includes amedia playback interface 1004 which includes standard media controls, such as affordances for pausing, reversing, or advancing media, affordances for controlling volume, and an affordance that displays and/or controls progress in media playback, in accordance with some embodiments. Theelectronic device 200 plays back the selected media; here, track 2 (“Piano Concerto # 2 in A) from the album “Liszt: The Piano Concertos.” - As illustrated in
FIG. 8C , a user requests media in a less specific manner than described with regard toFIG. 8A . Nonspecific unstructured natural language user input does not identify a particular media item with particularity. For example, a user wishes to hear a song associated with a popular movie, but does not know or recall the name of the song.User input 1010 is received, which identifies the movie but not the song: “play that song from Top Gun.” The user request made inFIG. 8C may be made at any time: during, after, before, or instead of playback of the media obtained as shown inFIG. 8B . Theuser input 1010 is displayed on thedisplay 212, in accordance with some embodiments. - Upon receiving nonspecific unstructured natural language user input requesting media, the digital assistant causes a search for that media to be performed, as described in greater detail with regard to
FIGS. 9A-9C . That search is performed utilizing the unstructured natural language user input, and the context of that input. The context of the user input may include one or more of device context, user context, and social context. - Device context includes information associated with the
electronic device 200 itself. In some embodiments, the device context includes the location of theelectronic device 200. A GPS system or other system may be used to localize theelectronic device 200, and may be able to determine whether the user is moving, where the user is located (e.g., home, school, work, park, gym), and other information. In accordance with some embodiments, theelectronic device 200 is configured to receive signals from a wireless location transmitter other than GPS, such as a Bluetooth® wireless location transmitter, or an iBeacon of Apple, Inc., Cupertino, Calif. As one example, the digital assistant determines that theelectronic device 200, and thus the user, is moving at a rate of speed consistent with automobile travel. The digital assistant utilizes this information in conjunction with user context (described below) that is related to the media most often played back by the user in the car in order to obtain requested media, in accordance with some embodiments. As another example, the digital assistant determines that theelectronic device 200 is at a venue in which live music is performed, such as an arena or a bar. In response, the digital assistant may cause a search for a schedule of musical performances at the location where theelectronic device 200 is located, and utilize that information to satisfy the user request for media, in accordance with some embodiments. As another example, where theelectronic device 200 is located in the user's home, and the user has not moved a detectable amount over a predetermined amount of time, the digital assistant determines that the user is at home watching television. - In accordance with some embodiments, the device context includes audio input from the microphone other than user speech, such as sound in the vicinity of the
electronic device 200. The electronic device, according to some embodiments, generates an acoustic fingerprint from that sound. An acoustic fingerprint is a condensed digital summary, generated from that sound, that can be used to identify that sound by comparing that acoustic fingerprint to a database. The electronic device, in other embodiments, also or instead converts that sound to text, where that sound includes recognizable speech. As an example of the use of such context, where the digital assistant has determined that the user is at home watching television (as described in the previous paragraph) other than via the electronic device, the digital assistant determines based on the sound in the vicinity of theelectronic device 200 that the user is watching a particular television program, such as through the Apple TV® digital media extender of Apple, Inc., Cupertino, Calif. The digital assistant also utilizes a database of television programming schedule information to make such a determination, in accordance with some embodiments. Upon receiving a request from a user for media (e.g., “record episodes of this show”; “get this song from the show”), the digital assistant utilizes location and ambient sound information to determine which media satisfies a user request. In accordance with another embodiment, in another example, the user is walking through a mall or public space, or sitting in a restaurant, and hears a song over the local sound system. In response to a user request to “add this song to my library,” the digital assistant may listen to ambient sound via themicrophone 213 in order to determine what the user meant by “this song.” Upon identifying the song, using, for example, acoustic fingerprinting or speech-to-text search techniques as described above, the digital assistant may add that song to a user library. - In accordance with some embodiments, the device context includes the content of media concurrently played by the
electronic device 200 at the same time as the user request for media. Such media can be in any format, such as audio and/or video. The video andmusic player module 252 accesses information associated with the media concurrently played by theelectronic device 200, in some embodiments, such that thedigital assistant 200 has direct access to that information. Such information is useful in contexts where the user requests media that is related to the media concurrently played by the electronic device (e.g., “play more like this,” “I want to hear the live version of this song”). In accordance with some embodiments, the device context includes a timecode associated with the content of media concurrently played by theelectronic device 200 at the same time as the user request for media. The digital assistant utilizes this timecode, in accordance with some embodiments, to determine the location in the media that is concurrent with the user request for media. For example, if a user is watching a video on the electronic device, and requests “add this artist to my stream,” the digital assistant accesses the media stream played by the video andmusic player module 252 to determine which media is being played concurrently, then uses the timecode of that media stream to determine if a song is associated with that timecode in the media stream; if so, the digital assistant determines that song is associated with the user input of “this artist,” and determines the artist who performed that song. Similarly, in accordance with some embodiments, theelectronic device 200 receives streaming audio from a source such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). If a user is listening to streaming audio, and does not recognize a particular song being played, the user may request information about that song, such as by typing or speaking “what song is this?” In response to the request, the digital assistant determines which song is playing, such as by inspecting metadata associated with the streaming audio, by generating an acoustic fingerprint from the streaming audio and comparing that acoustic fingerprint to a database (as described above), or by querying the server from which the streaming audio is received. The digital assistant then presents the song title and artist to the user, using text and/or audio. - In accordance with some embodiments, the device context includes data associated with media stored on the
electronic device 200. For example, the digital assistant infers that media stored on theelectronic device 200 is media that is preferred by a user, and utilizes that information in determining the meaning of nonspecific user requests for media. The data associated with media stored on the electronic device includes, for example, but is not limited to the presence of that media, bibliographic information of that media (e.g., title, album, release date), information relating to the playback history of that media (e.g., number of times the media has been played back; date the media was last played back; date the media was added to the electronic device), and metadata relating to that media. - In accordance with some embodiments, the device context includes the application context. Application context is related to the application the user is utilizing for media playback. For example, the digital assistant determines whether concurrent media playback is being performed by the video and
music player module 252, by a native application running on theelectronic device 200, by a third-party application associated with the electronic device 200 (e.g., HuluPlus® of Hulu, LLC, Santa Monica, Calif.), or by another application. The application context also includes metadata, if any, associated with the application. - User context includes information associated with the user of the
electronic device 200. User context includes the content of natural language user input requesting media. In accordance with some embodiments, user context includes demographic information about the user, such as the user's age, gender, or the like. The digital assistant uses this information to compare the request for media to similar requests made by other users with similar demographic profiles, in some embodiments. For example, a digital assistant receives nonspecific unstructured natural language user input requesting media from a user who attends college in Boston. The digital assistant causes a search to be made relating to media sought by other college students in Boston, and uses the popularity of media among similarly-situated users in order to obtain media for the user. - In accordance with some embodiments, the user context includes media associated with the user, regardless of the storage location of the media. Such media may be stored in the cloud, or may be associated with a streaming music service accessible to the user, such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). In some embodiments, the digital assistant infers that media associated with the user is media that is preferred by a user, and utilizes that information in determining the meaning of nonspecific user requests for media. In some embodiments, user context further includes data associated with the media associated with the user, such as but not limited to the presence of that media, bibliographic information of that media (e.g., title, album, release date), information relating to the playback history of that media (e.g., number of times the media has been played back; date the media was last played back; date the media was added to the electronic device), and metadata relating to that media.
- In accordance with some embodiments, the user context includes information relating to the musical preferences of the user. For example, the user context includes the history of media played back by the user, and/or the number of times the user has played back certain items, regardless of the storage location of those items. Media that has been played more often by the user is inferred to be preferred by the user, such that media that has been played frequently by the user that matches nonspecific natural language user input requesting media is considered a better match when determining a media item that satisfies a user request. As another example, the user context includes the history of media acquisition by the user, regardless of the storage location of that media. As another example, the user context includes the history of the addition of music to a streaming music service accessible to the user, such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.).
- In accordance with some embodiments, the user context includes data associated with user content accessible by the
electronic device 200. For example, user context includes data associated with digital photographs taken by the user, whether stored on theelectronic device 200, or stored remotely to and accessible by theelectronic device 200. Digital photographs typically are stored along with metadata such as the date taken and the location taken. Upon receiving nonspecific natural language user input requesting media such as “play hits from my trip to Italy,” the digital assistant may cause a search to be performed for information relating to a trip to Italy. Upon finding photograph metadata that includes a location within Italy, the digital assistant determines the corresponding date information in that photograph metadata. The digital assistant then causes a search to be made of databases of historical music chart information (e.g., the database of Billboard of New York, N.Y.) based on the date information obtained from the photograph. As is clear from this example, the user content need not be related to the type of media sought by the user. - Social context includes information associated with other users than the user of the
electronic device 200. As one example, social context includes how many times a particular media item has been streamed or downloaded from a music service such as iTunes® music service of Apple, Inc. of Cupertino, Calif. Such a count of streams or downloads is performed across an artist's musical output, in one example. Such a count is performed within an album, in another example. By way of a further example, the digital assistant may receive nonspecific natural language user input requesting media such as “play that song from Frozen.” The digital assistant may cause a search to be performed on the iTunes® music service of Apple, Inc. of Cupertino, Calif., in order to find a soundtrack album for the movie Frozen, and then determine which track on that album has been downloaded the greatest number of times. The particular media item on the album with the greatest number of downloads is obtained by the digital assistant. As another example, social context includes how many times a particular media item has been streamed from a streaming music service accessible to the user, such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). - In accordance with some embodiments, social context includes the number of references to a media item in a social media database. As one example, the digital assistant may receive nonspecific natural language user input requesting media such as “I want to hear that big hit from Famous Band.” Famous Band may have released a popular album with several hits. In order to disambiguate the user's request, the digital assistant may cause a search to be performed of a social database, e.g., the database of Twitter, Inc. of San Francisco, Calif., in order to determine how many mentions of a particular media item have been made across a recent period of time, such as the previous 7 days or 14 days. The particular media item from Famous Band with the most references in that period of time is obtained by the digital assistant.
- Returning specifically to
FIG. 8C ,user input 1010 has been received, which identifies a movie but not the requested song from the movie: “play that song from Top Gun.” The digital assistant identifies at least one context of theuser input 1010, as described above. According to some embodiments, the context is at least one of device context, user context and social context. The digital assistant causes a search for the media, based on the context and on the user input. For example, the digital assistant may search theelectronic device 200 and/or media associated with the user for the soundtrack for the movie “Top Gun.” Upon discovering the soundtrack, the digital assistant may determine which song on the soundtrack has been played the most, and determine that song satisfies the media request, after which the digital assistant obtains the song for the user. As another example, the digital assistant may search a music service for the soundtrack for the movie “Top Gun.” Upon discovering the soundtrack, the digital assistant may determine which song on the soundtrack has been streamed or downloaded the most times, and determine that song satisfies the media request, after which the digital assistant obtains the song for the user. - Both of these example processes, in addition to other processes, may be performed simultaneously in order to obtain the requested media. By performing the processes in parallel, rather than in series, the time to locate the media item is reduced, particularly where only one of several processes delivers a result that satisfies the user request. Further, where the parallel processes each deliver a single media item, confidence that it is the media item requested by the user is enhanced. Still further, where the parallel processes deliver two or more separate media items, the digital assistant applies further heuristics to those items to determine which is the most likely to meet the user request. The digital assistant may score each media item on one or more criteria, and determine that the media item with the highest score satisfies the user request, after which the digital assistant obtains the song for the user. The scoring methodology is biased toward certain results, such as results associated with media stored on the
electronic device 200, according to some embodiments. In some embodiments, a user selects which criteria are more or less important with regard to scoring in order to obtain the requested media. - As illustrated in
FIG. 8D , the digital assistant obtains the requested media. Theelectronic device 200 presents anidentifier 1012 associated with the media on thedisplay 212, in accordance with some embodiments, to allow the user to confirm which media is being played back: here, the song “Danger Zone” from Kenny Loggins, on the Top Gun Original Motion Picture Soundtrack Album. Theelectronic device 200 optionally includes amedia playback interface 1004 as described above. Theelectronic device 200 plays back the selected media. - The user may have had a different song in mind than the one presented in
FIG. 8D , or the user may simply change his or her mind about which media he or she would like to play back. As illustrated inFIG. 8E , the digital assistant receivesuser input 1020 requesting alternate media. In the example ofFIGS. 8C-8D , the alternate media is a different song from the same movie (i.e., the same soundtrack album). Theuser input 1020 need not be phrased as a request; as shown inFIG. 8E , theuser input 1020 states “No, I meant the other one.” The digital assistant performs speech-to-text conversion on theuser input 1020, and determines from the context of the most recent request and most recent digital assistant action that the user wishes to receive a different media item than the one most recently obtained. In response to receiving thesecond user input 1020, the digital assistant causes a search for the requested media based on the context, the user input, and the second user input. For example, the digital assistant may cause another search based on the same criteria as the first search, but where media items that match the first result (here, the song “Danger Zone”) are discarded as potential matches. As another example, the results of the previous search are still loaded in memory accessible to the digital assistant, and the digital assistant selects the next-highest match out of a list of possible matching media items. This approach may require more storage capacity but delivers faster results to the user. The digital assistant determines at least one additional media item that satisfies the request. As another example, theelectronic device 200 plays streaming media, such as streaming audio from Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). If the user wants to skip ahead to the next song, the user may request “skip this song,” “next song,” or the like. The digital assistant need not perform a search based on that request for media. Instead, according to some embodiments, the digital assistant transmits a signal to the server from which the streaming audio is received requesting that the stream skip ahead to the next song. In response, the digital assistant receives another song, which is then played by theelectronic device 200. - As illustrated in
FIG. 8F , the digital assistant obtains the media that satisfies the request. Theelectronic device 200 presents anidentifier 1022 associated with the media on thedisplay 212, in accordance with some embodiments, to allow the user to confirm which media is being played back: here, the song “Take My Breath Away (Love Theme from Top Gun)” from Berlin, on the Top Gun Original Motion Picture Soundtrack Album. Theelectronic device 200 optionally includes amedia playback interface 1004 as described above. Theelectronic device 200 plays back the selected media. - As illustrated in
FIG. 8G , the digital assistant receivesuser input 1030 requesting alternate media. In the example ofFIGS. 8E-8F , the alternate media is a different version of the song. In this example, the different version is a live version rather than a studio version. In other examples, the different version is a different studio version by the same artist, a different live version by the same artist, or the same song recorded by a different artist. The digital assistant causes a search for alternate media and determines at least one alternate media item that satisfies the request, in the same manner as described above with regard toFIGS. 8E-8F . - As illustrated in
FIG. 8H , the digital assistant obtains the media that satisfies the request. Theelectronic device 200 presents anidentifier 1032 associated with the media on thedisplay 212, in accordance with some embodiments, to allow the user to confirm which media is being played back: here, the song “Take My Breath Away Live” from Berlin, on the album entitled “Live: Sacred and Profane.” Theelectronic device 200 optionally includes amedia playback interface 1004 as described above. Theelectronic device 200 plays back the selected media. - In accordance with some embodiments, the digital assistant receives user input requesting media associated with a specific date in the past. Upon receiving nonspecific natural language user input requesting media such as “play popular music from my birthday,” the digital assistant causes a search to be performed for user context information relating to the user's birthday. According to some embodiments, the user's birthday is stored on the
electronic device 200, or is stored in association with a user account that in turn is associated with theelectronic device 200 and/or a service or program that transmits media to the electronic device, such as the iTunes® application program, Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). Upon determining the date of the user's birthday, the digital assistant then causes a search to be made of one or more databases of historical music chart information (e.g., the database of Billboard of New York, N.Y.) based on the date of the user's birthday. The digital assistant receives historical music chart information from one or more databases, and in response obtains for the user (through the use of streaming audio or by downloading) and plays one or more of the songs identified by that historical music chart information. - As another example, the user requests “play the top ten hits from 1978.” The digital assistant causes a search to be made of one or more databases of historical music chart information (e.g., the database of Billboard of New York, N.Y.) based on the specified date of 1978. The digital assistant receives historical music chart information from the one or more databases, and in response obtains for the user (through the use of streaming audio or by downloading) and plays the top ten songs of 1978, as identified by that historical music chart information. The digital assistant causes the songs to be played in countdown order, from the #10 hit “Three Times a Lady” by the Commodores, to #1 hit “Shadow Dancing” by Andy Gibb. Alternately, the digital assistant causes the songs to be played from #1 to #10, or plays the top ten songs in random order.
- In accordance with some embodiments, the digital assistant receives nonspecific user input requesting media associated with a particular artist. For example, the user requests “play the latest album from Famous Band.” The digital assistant causes a search to be made of one or more databases of music information (such as the iTunes® music service, or Apple Music, of Apple, Inc. of Cupertino, Calif.) based on the specified artist Famous Band. The digital assistant receives discography information from the one or more databases, including the name of the most recent album of Famous Band, and in response obtains for the user (through the use of streaming audio or by downloading) and plays the latest album from Famous Band. According to some embodiments, when utilizing a streaming media service such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.), the digital assistant initially queries the streaming media service for the latest album by the specified artist Famous Band, and in response receives an audio stream of the latest album by Famous Band.
- According to some embodiments, during media playback, the digital assistant receives input from a user associated with user satisfaction with the media. As one example, the
electronic device 200 receives speech or text input corresponding to a user liking the media (i.e., a “like”). A “like” input from the user is user context information. Optionally, the “like” input may be utilized as part of the social context with regard to other users. For example, if a user “likes” a particular media item, it may be inferred that others of similar demographic characteristics, and/or in a similar location, will be more interested in that particular media item. According to some embodiments, the user's “like” of a particular media item is stored locally on theelectronic device 200, is stored on the cloud in association with the user, or is part of a streaming music service accessible to the user, such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). - As another example, the
electronic device 200 receives speech or text input corresponding to a user disliking the media (i.e., a “dislike”). A “dislike” input from the user is user context information. Optionally, the “dislike” input may be utilized as part of the social context with regard to other users. For example, if a user “dislikes” a particular media item, it may be inferred that others of similar demographic characteristics, and/or in a similar location, will be less interested in that particular media item. According to some embodiments, the user's “dislike” of a particular media item is stored locally on theelectronic device 200, is stored on the cloud in association with the user, or is part of a streaming music service accessible to the user, such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). In some embodiments, upon receiving a “dislike” input, the digital assistant Upon receiving a “dislike” input, the digital assistant interrupts concurrent playback of media already playing on theelectronic device 200, skips ahead to the next media in a playback queue or media stream, ceases playing media, and/or takes other action, according to some embodiments. In some embodiments, a user request to skip a particular media item counts as a partial or complete “dislike” of that media item. In other embodiments, a user request to skip a media item is not counted as a “dislike” of that media item. - In accordance with some embodiments, the digital assistant receives user input requesting new music. For example, the user requests “play new music.” The digital assistant identifies at least one context of the user input, as described above. According to some embodiments, the context is at least one of device context, user context and social context. In response, according to some embodiments, the digital assistant transmits a request for new music to a streaming music service accessible to the user, such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). In response, the digital assistant receives an audio stream from the streaming music service, including one or more new songs (e.g., songs released in the past 14 days). According to some embodiments, selection of the one or more new songs in the audio is based at least in part on previous “like” and “dislike” inputs received from the user relative to other media, and/or other user context, device context, and/or social context.
- As another example, the user requests “play new country songs.” In response, according to some embodiments, the digital assistant transmits a request for new music in the genre of country to a streaming music service accessible to the user, such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). In response, the digital assistant receives an audio stream from the streaming music service, including one or more new country songs. According to some embodiments, selection of the one or more new country songs in the audio is based at least in part on previous “like” and “dislike” inputs received from the user relative to other media, and/or other user context, device context, and/or social context.
- In accordance with some embodiments, the digital assistant receives a user request to play additional similar media. For example, the user requests “play more like this.” The digital assistant identifies at least one context of the user input, as described above. According to some embodiments, the context is at least one of device context, user context and social context. In response to the user request, the digital assistant determines which song is playing, such as by inspecting metadata associated with the currently-playing audio, by generating an acoustic fingerprint from the streaming audio and comparing that acoustic fingerprint to a database (as described above), by querying a server from which streaming audio is received, and/or any other suitable action or actions. The digital assistant causes a search for the media, based on the context and on the user input. For example, the digital assistant may search the
electronic device 200 and/or media associated with the user for similar media, such as based on genre, artist, and user context of media that the user has previously “liked” or “disliked.” The digital assistant then obtains (from theelectronic device 200, from a streaming music service, or other source) media for the user. As another example, the digital assistant may search a music service for similar music. The digital assistant causes a search to be made of one or more databases of music information (such as the iTunes® music service, or Apple Music, of Apple, Inc. of Cupertino, Calif.) based on user context of media that the user has previously “liked” or “disliked,” the social context of media that other similar users have “liked” or “disliked,” and/or other context. The digital assistant receives information associated with songs from the one or more databases and in response obtains for the user (through the use of streaming audio or by downloading) and plays similar music. According to some embodiments, when utilizing a streaming media service such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.), the digital assistant initially queries the streaming media service for similar media, and in response receives an audio stream of similar media responsive to the user request. - When the digital assistant obtains media, the digital assistant interrupts concurrent playback of media already playing on the
electronic device 200, places the media in an ordered queue for later playback, adds the media to a media library, and/or takes other action, according to some embodiments. Referring back toFIGS. 8E-8F , the digital assistant determines based on theuser input 1020 that the returned media item did not satisfy the user request, in accordance with some embodiments. As a result, when thealternate media 1022 is obtained, it interrupts the concurrent playback of the song “Danger Zone,” terminating the playback of “Danger Zone” and replacing it with the playback ofalternate media 1022, in accordance with some embodiments. In general, according to some embodiments, when the digital assistant determines that the user input is consistent with input requesting an interruption of concurrently-played media, the digital assistant causes theelectronic device 200 to cease playing that media and replace it with the playback of the most-recently requested media. The media may be different types of media. For example, while watching a movie on theelectronic device 200, a user may request playback of a song; the digital assistant will cause theelectronic device 200 to cease playing the movie and replace it with the playback of the most-recently requested media—in this example, the song. - In accordance with some embodiments, when the digital assistant obtains media, the digital assistant places the media in an ordered queue for later playback. As illustrated in
FIG. 8J , the digital assistant receivesuser input 1040 requesting to “play more from this band.” The digital assistant determines based on theuser input 1040 that the user is satisfied with the media item previously obtained, because the user wishes to obtain more media from the same artist. Other criteria may be used to determine whetheruser input 1040 is consistent with user satisfaction with the media being played concurrently with theuser input 1040. Based on thatuser input 1040, the digital assistant causes a search to be made based on the user input and the context of the user input, determines one or more additional media items satisfying the user request, and obtains those one or more media items. As illustrated inFIG. 8K , the media playing concurrent with theuser input 1040 continues to play. The digital assistant causes the one or more additional media items to be placed in an ordered queue for playback. When the media playing concurrent with theuser input 1040 has completed playback, the first item in the ordered queue is then played. According to some embodiments, the items in the queue may be from the local library on theelectronic device 200, may be located external to the electronic device in the cloud, or may be part of a streaming music service accessible to the user, such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). In general, according to some embodiments, when the digital assistant determines that the user input is consistent with input reflecting user satisfaction with concurrently-playing media, the digital assistant causes theelectronic device 200 to continue playing that media and place one or more additional media items in an ordered queue for playback. The media may be different types of media, as set forth above with regard to another embodiment. - In accordance with some embodiments, when the digital assistant obtains media, the digital assistant adds the media to a media library associated with the user. In some examples, the media library is locally stored on the
electronic device 200, is stored on the cloud in association with the user, or is part of a streaming music service accessible to the user, such as Apple Music or iTunes Radio™ (services of Apple, Inc. of Cupertino, Calif.). For example, as illustrated inFIG. 8L , the digital assistant receivesuser input 1050 requesting “what is that song from Frozen?” The digital assistant causes a search for the media based on the user input and at least one context of the user input, determines at least one media item that satisfies the request, and obtains the at least one media item. In some embodiments, the digital assistant automatically adds the obtained at least one media item to a media library associated with the user. In other embodiments, as illustrated inFIG. 8M , upon obtaining the at least one media item, but before adding the at least one media item to a library associated with the user, the digital assistant presents the user with an option to add the at least one media item to a library associated with the user. According to some embodiments, the user is presented with anidentifier 1052 of the at least one media item obtained, along with arequest 1054 on thedisplay 212, such as “Add to library?” The electronic device displays afirst affordance 1056 associated with adding the at least one media item to a library associated with the user, and asecond affordance 1058 associated with not adding the at least one media item to a library associated with the user, in accordance with some embodiments. In response to user selection of thefirst affordance 1056, the digital assistant adds the at least one media item to a library associated with the user. - In accordance with some embodiments, as illustrated in
FIGS. 8N-8P , the digital assistant may receive user input that annotates a media item. Referring toFIG. 8N , theelectronic device 200 is playing backmedia item 1060, which in this example istrack 14 of the album “1970s Greatest Hits.” Theaudio interface 1004 may be displayed on thedisplay 212 concurrently with playback ofmedia item 1060. The user may wish to annotate themedia item 1060. In some embodiments, the digital assistant receivesuser input 1062 of unstructured natural language speech including one or more words, such as “I like these lyrics” or “What does this mean?”. Theuser input 1062 is associated with the timecode within themedia item 1060 at which time theuser input 1062 was received, according to some embodiments. Theuser input 1062 is converted from speech to text, stored as voice data, or handled in any other suitable manner. Theuser input 1062, in some embodiments, is a note from the user to himself or herself, or is other information upon which the digital assistant does not act. - In accordance with some embodiments, as illustrated in
FIG. 8Q , the digital assistant causes a search to be performed based on theuser input 1062 based on the context of theuser input 1062, according to some embodiments. In other embodiments, the digital assistant does not cause a search to be performed until receiving an express request from the user. In response to the search, the digital assistant provides thesearch result 1064 to the user on thedisplay 212. In this example, theuser input 1062 related to the meaning of the lyrics of themedia item 1060 at a particular timecode, and the digital assistant determined the meaning of the lyrics such as by reference to a lyrics database. -
FIGS. 9A-9C illustrate aprocess 900 for operating a digital assistant according to various examples. More specifically,process 900 can be implemented to perform media discovery based on nonspecific natural language user input using a digital assistant. Theprocess 900 can be performed using one or more electronic devices implementing a digital assistant. In some examples, theprocess 900 can be performed using a client-server system (e.g., system 100) implementing a digital assistant. The individual blocks of theprocess 900 may be distributed in any appropriate manner among one or more computers, systems, or electronic devices. For instances, in some examples,process 900 can be performed entirely on an electronic device (e.g.,devices process 900 is not limited to use with a smartphone; theprocess 900 may be implemented on any other suitable electronic device, such as a tablet, a desktop computer, a laptop, or a smart watch. Electronic devices with greater computing power and greater battery life may perform more of the blocks of theprocess 900. The distribution of blocks of theprocess 900 need not be fixed, and may vary depending upon network connection bandwidth, network connection quality, server load, availability of computer power and battery power at the electronic device (e.g., 104, 200, 400, 600), and/or other factors. Further, while the following discussion describesprocess 900 as being performed by a digital assistant system (e.g.,system 100 and/or digital assistant system 700), it should be recognized that the process or any particular part of the process is not limited to performance by any particular device, combination of devices, or implementation. The description of the process is further illustrated and exemplified byFIGS. 8A-8Q , and the description above related to those figures. -
FIGS. 9A-9C are a flow diagram 900 illustrating a method for discovering media based on a nonspecific, unstructured natural language request using a digital assistant and an electronic device (104, 200, 400, or 600) in accordance with some embodiments. Some operations inprocess 900 may be combined, the order of some operations may be changed, and some operations may be omitted. In particular, optional operations indicated with dashed-line shapes inFIGS. 9A-9C may be performed in any suitable order, if at all, and need not be performed in the order set forth inFIGS. 9A-9C . - As described below,
method 900 provides an intuitive way for discovering media based on a nonspecific, unstructured natural language request using a digital assistant. The method reduces the cognitive burden on a user for discovering media based on a nonspecific, unstructured natural language request using a digital assistant, thereby creating a more efficient human-machine interface. For battery-operated computing devices, enabling a user to discovering media based on a nonspecific, unstructured natural language request using a digital assistant more accurately and more efficiently conserves power and increases the time between battery charges. - At the beginning of
process 900, the digital assistant receives (902) user input associated with a request for media, where the user input includes unstructured natural language speech including one or more words. Where the electronic device (e.g., 104, 200, 400, 600) includes or is associated with amicrophone 213, that user input may be received through themicrophone 213. The user input may also be referred to as an audio input or audio stream. In some embodiments, the stream of audio can be received as raw sound waves, as an audio file, or in the form of a representative audio signal (analog or digital). In other embodiments, the audio stream can be received at a remote system, such as a server component of a digital assistant. The audio stream can include user speech, such as a spoken user request. The user input may include a spoken user request by an authorized user. In one example, the user input may be received from a user who is closely associated with the electronic device (104, 200, 400, 600) (e.g., the owner or predominant user of the user device). In an alternate embodiment, the user input is received in textual form instead of as speech. In some embodiments, the audio stream is converted from speech to text by ASR processing prior to, or during, analysis by the digital assistant. Such conversion may be performed as described above, such as in paragraphs [0175] et seq. of this document. - The digital assistant identifies (904) at least one context associated with the user input. As set forth above with regard to
FIGS. 8A-8Q , in accordance with some embodiments the context includes one or more of device context, user context, and social context. Examples of each context and its use in media discovery are also set forth above. - After identifying at least one context associated with the user input, the digital assistant causes (906) a search for the requested media based on the at least one context and the user input. In some embodiments, the search is performed by the digital assistant itself. In other embodiments, the search is requested by the digital assistant from a separate entity that performs the search and returns the results to the digital assistant. In some embodiments, the search is both performed by the digital assistant itself and requested by the digital assistant from a separate entity. By performing both searches in parallel, response time to the user request of (902) is reduced.
- The search of
block 906 may be performed locally, on the electronic device (e.g., 104, 200, 400, 600), in accordance with some embodiments. In accordance with other embodiments, the search ofblock 906 may be performed remotely to the electronic device (e.g., 104, 200, 400, 600). A search performed remotely to the electronic device (e.g., 104, 200, 400, 600) may be performed at a server that includes or possesses access to information relative to the search, such as a server of Shazam Entertainment Limited of London, United Kingdom for audio fingerprint information, a server of Billboard Magazine of New York, N.Y. for historical music information, and/or a server of the iTunes® music service of Apple, Inc. of Cupertino, Calif. In some embodiments, the search is both performed locally and remotely to the electronic device (e.g., 104, 200, 400, 600). By performing multiple searches in parallel, response time to the user request of (902) is reduced. - The digital assistant determines (908), based on the at least one context and the user input, at least one media item that satisfies the request. The digital assistant makes this determination in any suitable manner. According to some embodiments, the digital assistant selects the first match that exceeds a predetermined threshold. The digital assistant determines (910) a probability, based on the at least one context and the user input, that at least one media item satisfies the request. Next, the digital assistant determines (912) whether the probability exceeds a threshold. In some embodiments, the threshold may be predetermined. In other embodiments, the threshold may be user-adjustable. In other embodiments, the threshold may be dynamically variable. If the media items exceed the threshold, the
process 900 proceeds to thenext block 918. According to some embodiments, the digital assistant selects the best match of several candidate matches. The digital assistant determines (914) a probability, based on the at least one context and the user input, that at least one media item satisfies the request. Next, the digital assistant selects the media item having the highest probability, and proceeds to thenext block 918. Examples of thedetermination 908, based on the at least one context and the user input, of at least one media item that satisfies the request ofblock 902, are also provided above relative toFIGS. 8A-8Q . - In accordance with a determination that the at least one media item satisfies the request, the digital assistant obtains (918) the at least one media item. In accordance with some embodiments, the digital assistant can obtain the at least one media item in several ways. As one example, the digital assistant automatically adds (920) the obtained at least one media item to a media library associated with the user, as described above with regard to
FIGS. 8A-8Q . As another example, the digital assistant presents (922) the user with an option to add the obtained media to a media library associated with the user, and in response to user selection of the option to add the obtained media to a media library associated with the user, adds (924) the obtained media to a media library associated with the user. This process is described above, with particular reference toFIGS. 8L-8M and the accompanying text in the specification. As another example, the digital assistant places (926) the obtained media in an ordered queue, and then plays (928) the media according to the queue. This process is described above, with particular reference toFIGS. 8J-8K and the accompanying text in the specification. In accordance with some embodiments, in the obtainingblock 918, the digital assistant may determine (930) whether a local library includes the at least one media item. The local library is located on the electronic device (e.g., 104, 200, 400, 600). By searching the local library first, or in parallel with causing an external search, the amount of time required to satisfy the user request is reduced when the requested item is located on the electronic device (e.g., 104, 200, 400, 600). If the digital assistant determines that the local library includes the at least one media item, the digital assistant presents (932) the at least one media item to the user. If the digital assistant determines that the local library does not include the at least one media item, the digital assistant obtains (934) the at least one media item from an external data source. - In conjunction with obtaining (918) the at least one media item, or after obtaining (918) the media item, in some embodiments the digital assistant plays (936) the media item. In some circumstances, where the digital assistant determines that the user wishes to interrupt the concurrent playback of other media, the digital assistant terminates (938) the concurrent playback of other media, as described above with regard to
FIGS. 8A-8Q . - In accordance with some embodiments, after obtaining the media item, the digital assistant receives (940) a second user input including unstructured natural language speech including one or more words. The digital assistant annotates (942) the media item with the one or more words. In some embodiments, the process stops here, if the user desires simply to make and retain a note in association with the media item. In other embodiments, the process continues, and the digital assistant causes (944) a search to be performed based on the annotation. Upon receipt of search results, the digital assistant presents (946) the search result to the user. This process is described above, with particular reference to
FIGS. 8N-8Q and the accompanying text in the specification. - In accordance with some embodiments, the digital assistant receives (948) a second user input requesting user material. As one example, this may occur when the digital assistant originally obtained a media item that did not match the user's request. This situation is described above, with particular reference to
FIGS. 8E-8F and the accompanying text in the specification. As another example, this may occur when the digital assistant originally obtained a media item that matched a user's request, but user wishes to hear different media. This situation is described above, with particular reference toFIGS. 8G-8H and the accompanying text in the specification. In response to receiving the second user input, the digital assistant causes (950) a search for the media based on the at least one context, the user input, and the second user input. As one example, the combination of the user input and the second user input provides additional search criteria that are useful in determining the media item. As another example, the combination of the user input and the second user input allows the digital assistant to exclude the original result when evaluating search results. The digital assistant determines (952), based on the at least one context, the user input and the second user input, at least one additional media item that satisfies the request. In accordance with a determination that the at least one additional media item satisfies the request, the digital assistant obtains (954) the at least one additional media item. Further, in accordance with some embodiments, the probability that a media item satisfies the request for media can be updated over time, based on, for example, the at least one context, the user input, and the second user input requesting user material. - In accordance with some embodiments,
FIG. 10 shows an exemplary functional block diagram of anelectronic device 1000 configured in accordance with the principles of the various described embodiments. In accordance with some embodiments, the functional blocks ofelectronic device 1000 are configured to perform the techniques described above. The functional blocks of thedevice 1000 are, optionally, implemented by hardware, software, or a combination of hardware and software to carry out the principles of the various described examples. It is understood by persons of skill in the art that the functional blocks described inFIG. 10 are, optionally, combined or separated into sub-blocks to implement the principles of the various described examples. Therefore, the description herein optionally supports any possible combination or separation or further definition of the functional blocks described herein. - As shown in
FIG. 10 , anelectronic device 1000 includes adisplay unit 1002 configured to display a graphic user interface, optionally, a touch-sensitive surface unit 1004 configured to receive contacts, amicrophone unit 1006 configured to receive audio signals, and aprocessing unit 1008 coupled to thedisplay unit 1002 and, optionally, the touch-sensitive surface unit 1004 andmicrophone unit 1006. In some embodiments, theprocessing unit 1008 includes areceiving unit 1010, an identifyingunit 1012, a causingunit 1014, a determiningunit 1016, an obtainingunit 1018, and aplaying unit 1020. - The processing unit is configured to receive (e.g., with receiving unit 1010) user input associated with a request for media, the user input comprising unstructured natural language speech including one or more words; identify (e.g., with identifying unit 1012) at least one context associated with the user input; cause (e.g., with causing unit 1014) a search for the media based on the at least one context and the user input; determine (e.g., with determining unit 1016) based on the at least one context and the user input, at least one media item that satisfies the request; and in accordance with a determination that the at least one media item satisfies the request, obtain (e.g., with obtaining unit 1018) the at least one media item.
- In some embodiments, the causing unit is further configured to cause (e.g., with causing unit 1014) searching to be performed locally on the device.
- In some embodiments, the causing unit is further configured to cause (e.g., with causing unit 1014) searching to be performed remotely to the device.
- In some embodiments, the processing unit is further configured to determine (e.g., with determining unit 1016) whether a local library includes the media item; and in accordance with a determination that the local library includes the media item, present (e.g., with playing unit 1020) the media item to the user; in accordance with a determination that the local library does not include the media item, obtain (e.g., with obtaining unit 1018) the media item from an external data source.
- In some embodiments, the processing unit is further configured to receive (e.g., with receiving unit 1010) second user input requesting alternate media; in response to receiving the second user input, cause (e.g., with causing unit 1014) a search for the media based on the at least one context, the user input and the second user input; determine (e.g., with determining unit 1016) based on the at least one context, the user input and the second user input, at least one additional media item that satisfies the request; and in accordance with a determination that the at least one additional media item satisfies the request, obtain (e.g., with obtaining unit 1018) the at least one additional media item.
- In some embodiments, the at least one context associated with the user input includes a device context.
- In some embodiments, the device context includes the location of the device.
- In some embodiments, the device context includes the proximity of the device to a wireless location transmitter.
- In some embodiments, the device context includes the content of media concurrently played by the device.
- In some embodiments, the device context includes a timecode associated with media concurrently played by the device.
- In some embodiments, the device context includes audio input from the microphone other than user speech.
- In some embodiments, the device context includes data associated with media stored on the device.
- In some embodiments, the device context includes application context.
- In some embodiments, the at least one context associated with the user input includes a user context.
- In some embodiments, the user context includes the content of the user input.
- In some embodiments, the user context includes media associated with the user.
- In some embodiments, the user context includes demographic information about the user.
- In some embodiments, the user context includes information relating to the musical preferences of the user.
- In some embodiments, the user context includes data associated with user content accessible by the device.
- In some embodiments, the at least one context associated with the user input includes a social context.
- In some embodiments, the social context includes the access frequency of a particular media item across a plurality of users.
- In some embodiments, the social context includes the number of references to a media item in a social media database.
- In some embodiments, the media item is a song.
- In some embodiments, the processing unit is further configured to, in response to obtaining the at least one media item, play (e.g., with playing unit 1020) at least one media item, and terminate (e.g., with playing unit 1020) concurrent playback of other media.
- In some embodiments, the processing unit is further configured to, in response to obtaining the media item, place (e.g., with playing unit 1020) the at least one obtained media item in an ordered queue; and play (e.g., with playing unit 1020) the at least one media item according to the queue.
- In some embodiments, the obtaining unit is further configured to add the at least one media item to a media library associated with the user.
- In some embodiments, the processing unit is further configured to present (e.g., with the display unit 1002) the user with an option to add the at least one media item to a media library associated with the user; and in response to user selection of the option to add the at least one media item to a media library associated with the user, add (e.g., with the obtaining unit 1018) the at least one media item to a media library associated with the user.
- In some embodiments, the processing unit is further configured to, after obtaining the media item, receive (e.g., with the receiving unit 1010) second user input comprising unstructured natural language speech including one or more words; and annotate (e.g. with the processing unit 1008) the media item with the one or more words.
- In some embodiments, the processing unit is further configured to cause (e.g., with the causing unit 1014) a search to be performed based on the annotation; and present (e.g., with the display unit 1002) the search result to the user.
- In some embodiments, the determining unit is further configured to determine (e.g., with the determining unit 1016) a probability, based on the at least one context and the user input, that at least one media item satisfies the request; and determine (e.g., with the determining unit 1016) whether the probability exceeds a threshold.
- In some embodiments, the determining unit is further configured to determine (e.g., with the determining unit 1016) a probability, based on the at least one context and the user input, that at least one media item satisfies the request; and selecting (e.g., with the determining unit 1016) the media item having the highest probability.
- In some embodiments, the receiving unit is further configured to receive streaming audio containing the at least one media item.
- The operations described above with reference to
FIGS. 9A-9C are, optionally, implemented by components depicted inFIGS. 1A-7C orFIG. 10 . It would be clear to a person having ordinary skill in the art how processes can be implemented based on the components depicted inFIGS. 1A-7C orFIG. 10 . - The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the techniques and their practical applications. Others skilled in the art are thereby enabled to best utilize the techniques and various embodiments with various modifications as are suited to the particular use contemplated.
- Although the disclosure and examples have been fully described with reference to the accompanying drawings, it is to be noted that various changes and modifications will become apparent to those skilled in the art. Such changes and modifications are to be understood as being included within the scope of the disclosure and examples as defined by the claims.
- As described above, one aspect of the present technology is the gathering and use of data available from various sources to improve the delivery to users of content that may be of interest to them. The present disclosure contemplates that in some instances, this gathered data may include personal information data that uniquely identifies or can be used to contact or locate a specific person. Such personal information data can include demographic data, location-based data, telephone numbers, email addresses, home addresses, or any other identifying information.
- The present disclosure recognizes that the use of such personal information data, in the present technology, can be used to the benefit of users. For example, the personal information data can be used to deliver targeted content that is of greater interest to the user. Accordingly, use of such personal information data enables calculated control of the delivered content. Further, other uses for personal information data that benefit the user are also contemplated by the present disclosure.
- The present disclosure further contemplates that the entities responsible for the collection, analysis, disclosure, transfer, storage, or other use of such personal information data will comply with well-established privacy policies and/or privacy practices. In particular, such entities should implement and consistently use privacy policies and practices that are generally recognized as meeting or exceeding industry or governmental requirements for maintaining personal information data private and secure. For example, personal information from users should be collected for legitimate and reasonable uses of the entity and not shared or sold outside of those legitimate uses. Further, such collection should occur only after receiving the informed consent of the users. Additionally, such entities would take any needed steps for safeguarding and securing access to such personal information data and ensuring that others with access to the personal information data adhere to their privacy policies and procedures. Further, such entities can subject themselves to evaluation by third parties to certify their adherence to widely accepted privacy policies and practices.
- Despite the foregoing, the present disclosure also contemplates embodiments in which users selectively block the use of, or access to, personal information data. That is, the present disclosure contemplates that hardware and/or software elements can be provided to prevent or block access to such personal information data. For example, in the case of advertisement delivery services, the present technology can be configured to allow users to select to “opt in” or “opt out” of participation in the collection of personal information data during registration for services. In another example, users can select not to provide location information for targeted content delivery services. In yet another example, users can select to not provide precise location information, but permit the transfer of location zone information.
- Therefore, although the present disclosure broadly covers use of personal information data to implement one or more various disclosed embodiments, the present disclosure also contemplates that the various embodiments can also be implemented without the need for accessing such personal information data. That is, the various embodiments of the present technology are not rendered inoperable due to the lack of all or a portion of such personal information data. For example, content can be selected and delivered to users by inferring preferences based on non-personal information data or a bare minimum amount of personal information, such as the content being requested by the device associated with a user, other non-personal information available to the content delivery services, or publically available information.
Claims (30)
Priority Applications (8)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US14/819,343 US20160378747A1 (en) | 2015-06-29 | 2015-08-05 | Virtual assistant for media playback |
CN202110585353.2A CN113392239A (en) | 2015-06-29 | 2016-03-31 | Virtual assistant for media playback |
CN201680031457.6A CN107615276B (en) | 2015-06-29 | 2016-03-31 | Virtual assistant for media playback |
EP16818374.7A EP3289493A4 (en) | 2015-06-29 | 2016-03-31 | Virtual assistant for media playback |
PCT/US2016/025404 WO2017003535A1 (en) | 2015-06-29 | 2016-03-31 | Virtual assistant for media playback |
EP19180842.7A EP3564831A1 (en) | 2015-06-29 | 2016-03-31 | Virtual assistant for media playback |
US16/360,695 US11010127B2 (en) | 2015-06-29 | 2019-03-21 | Virtual assistant for media playback |
US17/226,988 US20210224032A1 (en) | 2015-06-29 | 2021-04-09 | Virtual assistant for media playback |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201562186182P | 2015-06-29 | 2015-06-29 | |
US14/819,343 US20160378747A1 (en) | 2015-06-29 | 2015-08-05 | Virtual assistant for media playback |
Related Child Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US16/360,695 Continuation US11010127B2 (en) | 2015-06-29 | 2019-03-21 | Virtual assistant for media playback |
Publications (1)
Publication Number | Publication Date |
---|---|
US20160378747A1 true US20160378747A1 (en) | 2016-12-29 |
Family
ID=57602373
Family Applications (3)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US14/819,343 Abandoned US20160378747A1 (en) | 2015-06-29 | 2015-08-05 | Virtual assistant for media playback |
US16/360,695 Active US11010127B2 (en) | 2015-06-29 | 2019-03-21 | Virtual assistant for media playback |
US17/226,988 Pending US20210224032A1 (en) | 2015-06-29 | 2021-04-09 | Virtual assistant for media playback |
Family Applications After (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US16/360,695 Active US11010127B2 (en) | 2015-06-29 | 2019-03-21 | Virtual assistant for media playback |
US17/226,988 Pending US20210224032A1 (en) | 2015-06-29 | 2021-04-09 | Virtual assistant for media playback |
Country Status (4)
Country | Link |
---|---|
US (3) | US20160378747A1 (en) |
EP (2) | EP3289493A4 (en) |
CN (2) | CN107615276B (en) |
WO (1) | WO2017003535A1 (en) |
Cited By (165)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20170083584A1 (en) * | 2015-09-23 | 2017-03-23 | Motorola Solutions, Inc. | Apparatus, system, and method for responding to a user-initiated query with a context-based response |
US9747083B1 (en) * | 2017-01-23 | 2017-08-29 | Essential Products, Inc. | Home device application programming interface |
US20170249519A1 (en) * | 2014-05-23 | 2017-08-31 | Samsung Electronics Co., Ltd. | Method and device for reproducing content |
CN107507615A (en) * | 2017-08-29 | 2017-12-22 | 百度在线网络技术(北京)有限公司 | Interface intelligent interaction control method, device, system and storage medium |
US9865248B2 (en) | 2008-04-05 | 2018-01-09 | Apple Inc. | Intelligent text-to-speech conversion |
US9934785B1 (en) * | 2016-11-30 | 2018-04-03 | Spotify Ab | Identification of taste attributes from an audio signal |
US9966060B2 (en) | 2013-06-07 | 2018-05-08 | Apple Inc. | System and method for user-specified pronunciation of words for speech synthesis and recognition |
US9986419B2 (en) | 2014-09-30 | 2018-05-29 | Apple Inc. | Social reminders |
US9990176B1 (en) * | 2016-06-28 | 2018-06-05 | Amazon Technologies, Inc. | Latency reduction for content playback |
US10043516B2 (en) | 2016-09-23 | 2018-08-07 | Apple Inc. | Intelligent automated assistant |
US10049675B2 (en) | 2010-02-25 | 2018-08-14 | Apple Inc. | User profiling for voice input processing |
US10079014B2 (en) | 2012-06-08 | 2018-09-18 | Apple Inc. | Name recognition system |
US10083690B2 (en) | 2014-05-30 | 2018-09-25 | Apple Inc. | Better resolution when referencing to concepts |
US20180277133A1 (en) * | 2015-11-20 | 2018-09-27 | Synaptics Incorporated | Input/output mode control for audio processing |
US10108612B2 (en) | 2008-07-31 | 2018-10-23 | Apple Inc. | Mobile device having human language translation capability with positional feedback |
US20180332432A1 (en) * | 2016-01-21 | 2018-11-15 | Google Llc | Sharing Navigation Data Among Co-Located Computing Devices |
WO2018212885A1 (en) * | 2017-05-16 | 2018-11-22 | Apple Inc. | Intelligent automated assistant for media exploration |
US10147426B1 (en) | 2017-08-01 | 2018-12-04 | Lenovo (Singapore) Pte. Ltd. | Method and device to select an audio output circuit based on priority attributes |
WO2019010138A1 (en) * | 2017-07-03 | 2019-01-10 | Google Llc | Obtaining responsive information from multiple corpora |
US20190019035A1 (en) * | 2015-09-07 | 2019-01-17 | Lg Electronics Inc. | Mobile terminal and method for operating the same |
US20190095444A1 (en) * | 2017-09-22 | 2019-03-28 | Amazon Technologies, Inc. | Voice driven analytics |
US20190114137A1 (en) * | 2017-10-12 | 2019-04-18 | Hyundai Motor Company | Apparatus and method for processing user input for vehicle |
US20190146994A1 (en) * | 2016-05-09 | 2019-05-16 | Audiocoup B.V. | System for determining user exposure to audio fragments |
US10297255B2 (en) | 2017-01-23 | 2019-05-21 | Bank Of America Corporation | Data processing system with machine learning engine to provide automated collaboration assistance functions |
US10311871B2 (en) | 2015-03-08 | 2019-06-04 | Apple Inc. | Competing devices responding to voice triggers |
US10311144B2 (en) | 2017-05-16 | 2019-06-04 | Apple Inc. | Emoji word sense disambiguation |
US10332518B2 (en) | 2017-05-09 | 2019-06-25 | Apple Inc. | User interface for correcting recognition errors |
US10356243B2 (en) | 2015-06-05 | 2019-07-16 | Apple Inc. | Virtual assistant aided communication with 3rd party service in a communication session |
US10354652B2 (en) | 2015-12-02 | 2019-07-16 | Apple Inc. | Applying neural network language models to weighted finite state transducers for automatic speech recognition |
US10365932B2 (en) | 2017-01-23 | 2019-07-30 | Essential Products, Inc. | Dynamic application customization for automated environments |
US10381016B2 (en) | 2008-01-03 | 2019-08-13 | Apple Inc. | Methods and apparatus for altering audio output signals |
US10395654B2 (en) | 2017-05-11 | 2019-08-27 | Apple Inc. | Text normalization based on a data-driven learning network |
US10403278B2 (en) | 2017-05-16 | 2019-09-03 | Apple Inc. | Methods and systems for phonetic matching in digital assistant services |
US10403283B1 (en) | 2018-06-01 | 2019-09-03 | Apple Inc. | Voice interaction at a primary device to access call functionality of a companion device |
US10410637B2 (en) | 2017-05-12 | 2019-09-10 | Apple Inc. | User-specific acoustic models |
US10417344B2 (en) | 2014-05-30 | 2019-09-17 | Apple Inc. | Exemplar-based natural language processing |
US10417266B2 (en) | 2017-05-09 | 2019-09-17 | Apple Inc. | Context-aware ranking of intelligent response suggestions |
US10417405B2 (en) | 2011-03-21 | 2019-09-17 | Apple Inc. | Device access using voice authentication |
CN110288987A (en) * | 2018-03-19 | 2019-09-27 | 三星电子株式会社 | Method for handling the system of voice data and controlling the system |
US10431204B2 (en) | 2014-09-11 | 2019-10-01 | Apple Inc. | Method and apparatus for discovering trending terms in speech requests |
US10438595B2 (en) | 2014-09-30 | 2019-10-08 | Apple Inc. | Speaker identification and unsupervised speaker adaptation techniques |
US10445429B2 (en) | 2017-09-21 | 2019-10-15 | Apple Inc. | Natural language understanding using vocabularies with compressed serialized tries |
US10453443B2 (en) | 2014-09-30 | 2019-10-22 | Apple Inc. | Providing an indication of the suitability of speech recognition |
US10460734B2 (en) * | 2018-03-08 | 2019-10-29 | Frontive, Inc. | Methods and systems for speech signal processing |
US10474753B2 (en) | 2016-09-07 | 2019-11-12 | Apple Inc. | Language identification using recurrent neural networks |
US10482874B2 (en) | 2017-05-15 | 2019-11-19 | Apple Inc. | Hierarchical belief states for digital assistants |
US10496705B1 (en) | 2018-06-03 | 2019-12-03 | Apple Inc. | Accelerated task performance |
US10497365B2 (en) | 2014-05-30 | 2019-12-03 | Apple Inc. | Multi-command single utterance input method |
US10529332B2 (en) | 2015-03-08 | 2020-01-07 | Apple Inc. | Virtual assistant activation |
US10567477B2 (en) | 2015-03-08 | 2020-02-18 | Apple Inc. | Virtual assistant continuity |
US10580409B2 (en) | 2016-06-11 | 2020-03-03 | Apple Inc. | Application integration with a digital assistant |
US10592604B2 (en) | 2018-03-12 | 2020-03-17 | Apple Inc. | Inverse text normalization for automatic speech recognition |
US10593346B2 (en) | 2016-12-22 | 2020-03-17 | Apple Inc. | Rank-reduced token representation for automatic speech recognition |
US10600409B2 (en) | 2017-06-09 | 2020-03-24 | Google Llc | Balance modifications of audio-based computer program output including a chatbot selected based on semantic processing of audio |
US10614122B2 (en) | 2017-06-09 | 2020-04-07 | Google Llc | Balance modifications of audio-based computer program output using a placeholder field based on content |
US10636424B2 (en) | 2017-11-30 | 2020-04-28 | Apple Inc. | Multi-turn canned dialog |
US10643611B2 (en) | 2008-10-02 | 2020-05-05 | Apple Inc. | Electronic devices with voice command and contextual data processing capabilities |
US10652170B2 (en) * | 2017-06-09 | 2020-05-12 | Google Llc | Modification of audio-based computer program output |
US10657961B2 (en) | 2013-06-08 | 2020-05-19 | Apple Inc. | Interpreting and acting upon commands that involve sharing information with remote devices |
US10657328B2 (en) | 2017-06-02 | 2020-05-19 | Apple Inc. | Multi-task recurrent neural network architecture for efficient morphology handling in neural language modeling |
US10657173B2 (en) | 2017-06-09 | 2020-05-19 | Google Llc | Validate modification of audio-based computer program output |
CN111225261A (en) * | 2018-11-27 | 2020-06-02 | Lg电子株式会社 | Multimedia device for processing voice command and control method thereof |
US10685183B1 (en) * | 2018-01-04 | 2020-06-16 | Facebook, Inc. | Consumer insights analysis using word embeddings |
US10684703B2 (en) | 2018-06-01 | 2020-06-16 | Apple Inc. | Attention aware virtual assistant dismissal |
US10699717B2 (en) | 2014-05-30 | 2020-06-30 | Apple Inc. | Intelligent assistant for home automation |
US10714117B2 (en) | 2013-02-07 | 2020-07-14 | Apple Inc. | Voice trigger for a digital assistant |
US10726832B2 (en) | 2017-05-11 | 2020-07-28 | Apple Inc. | Maintaining privacy of personal information |
US10733993B2 (en) | 2016-06-10 | 2020-08-04 | Apple Inc. | Intelligent digital assistant in a multi-tasking environment |
US10733375B2 (en) | 2018-01-31 | 2020-08-04 | Apple Inc. | Knowledge-based framework for improving natural language understanding |
US10733982B2 (en) | 2018-01-08 | 2020-08-04 | Apple Inc. | Multi-directional dialog |
US10741185B2 (en) | 2010-01-18 | 2020-08-11 | Apple Inc. | Intelligent automated assistant |
US10748546B2 (en) | 2017-05-16 | 2020-08-18 | Apple Inc. | Digital assistant services based on device capabilities |
US10755703B2 (en) | 2017-05-11 | 2020-08-25 | Apple Inc. | Offline personal assistant |
US10755051B2 (en) | 2017-09-29 | 2020-08-25 | Apple Inc. | Rule-based natural language processing |
US10769385B2 (en) | 2013-06-09 | 2020-09-08 | Apple Inc. | System and method for inferring user intent from speech inputs |
US10777203B1 (en) | 2018-03-23 | 2020-09-15 | Amazon Technologies, Inc. | Speech interface device with caching component |
US10789945B2 (en) | 2017-05-12 | 2020-09-29 | Apple Inc. | Low-latency intelligent automated assistant |
US10791176B2 (en) | 2017-05-12 | 2020-09-29 | Apple Inc. | Synchronization and task delegation of a digital assistant |
US10789959B2 (en) | 2018-03-02 | 2020-09-29 | Apple Inc. | Training speaker recognition models for digital assistants |
US10810274B2 (en) | 2017-05-15 | 2020-10-20 | Apple Inc. | Optimizing dialogue policy decisions for digital assistants using implicit feedback |
US10818288B2 (en) | 2018-03-26 | 2020-10-27 | Apple Inc. | Natural assistant interaction |
US10839159B2 (en) | 2018-09-28 | 2020-11-17 | Apple Inc. | Named entity normalization in a spoken dialog system |
CN112041787A (en) * | 2018-06-15 | 2020-12-04 | 三星电子株式会社 | Electronic device for outputting response to user input using application and method of operating the same |
US10892996B2 (en) | 2018-06-01 | 2021-01-12 | Apple Inc. | Variable latency device coordination |
US10904611B2 (en) | 2014-06-30 | 2021-01-26 | Apple Inc. | Intelligent automated assistant for TV user interactions |
US10909331B2 (en) | 2018-03-30 | 2021-02-02 | Apple Inc. | Implicit identification of translation payload with neural machine translation |
US10928918B2 (en) | 2018-05-07 | 2021-02-23 | Apple Inc. | Raise to speak |
US20210063190A1 (en) * | 2019-08-29 | 2021-03-04 | Subaru Corporation | Information processor, information processing method, audio output system, and computer-readable recording medium |
US10942703B2 (en) | 2015-12-23 | 2021-03-09 | Apple Inc. | Proactive assistance based on dialog communication between devices |
US10942702B2 (en) | 2016-06-11 | 2021-03-09 | Apple Inc. | Intelligent device arbitration and control |
US10956666B2 (en) | 2015-11-09 | 2021-03-23 | Apple Inc. | Unconventional virtual assistant interactions |
US10972297B2 (en) | 2017-01-23 | 2021-04-06 | Bank Of America Corporation | Data processing system with machine learning engine to provide automated collaboration assistance functions |
US20210104220A1 (en) * | 2019-10-08 | 2021-04-08 | Sarah MENNICKEN | Voice assistant with contextually-adjusted audio output |
US10984799B2 (en) | 2018-03-23 | 2021-04-20 | Amazon Technologies, Inc. | Hybrid speech interface device |
US10984780B2 (en) | 2018-05-21 | 2021-04-20 | Apple Inc. | Global semantic word embeddings using bi-directional recurrent neural networks |
US11010561B2 (en) | 2018-09-27 | 2021-05-18 | Apple Inc. | Sentiment prediction from textual data |
US11010127B2 (en) | 2015-06-29 | 2021-05-18 | Apple Inc. | Virtual assistant for media playback |
US11025565B2 (en) | 2015-06-07 | 2021-06-01 | Apple Inc. | Personalized prediction of responses for instant messaging |
US11023513B2 (en) | 2007-12-20 | 2021-06-01 | Apple Inc. | Method and apparatus for searching using an active ontology |
US11048473B2 (en) | 2013-06-09 | 2021-06-29 | Apple Inc. | Device, method, and graphical user interface for enabling conversation persistence across two or more instances of a digital assistant |
US11069336B2 (en) | 2012-03-02 | 2021-07-20 | Apple Inc. | Systems and methods for name pronunciation |
US11070949B2 (en) | 2015-05-27 | 2021-07-20 | Apple Inc. | Systems and methods for proactively identifying and surfacing relevant content on an electronic device with a touch-sensitive display |
US11069347B2 (en) | 2016-06-08 | 2021-07-20 | Apple Inc. | Intelligent automated assistant for media exploration |
US11120372B2 (en) | 2011-06-03 | 2021-09-14 | Apple Inc. | Performing actions associated with task items that represent tasks to perform |
US11127397B2 (en) | 2015-05-27 | 2021-09-21 | Apple Inc. | Device voice control |
US11126400B2 (en) | 2015-09-08 | 2021-09-21 | Apple Inc. | Zero latency digital assistant |
US11133008B2 (en) | 2014-05-30 | 2021-09-28 | Apple Inc. | Reducing the need for manual start/end-pointing and trigger phrases |
US11140099B2 (en) | 2019-05-21 | 2021-10-05 | Apple Inc. | Providing message response suggestions |
US11145294B2 (en) | 2018-05-07 | 2021-10-12 | Apple Inc. | Intelligent automated assistant for delivering content from user experiences |
US20210334306A1 (en) * | 2018-05-03 | 2021-10-28 | Google Llc | Coordination of overlapping processing of audio queries |
US11170166B2 (en) | 2018-09-28 | 2021-11-09 | Apple Inc. | Neural typographical error modeling via generative adversarial networks |
EP3910495A1 (en) * | 2020-05-12 | 2021-11-17 | Apple Inc. | Reducing description length based on confidence |
WO2021231197A1 (en) * | 2020-05-12 | 2021-11-18 | Apple Inc. | Reducing description length based on confidence |
US20210357172A1 (en) * | 2020-05-12 | 2021-11-18 | Apple Inc. | Reducing description length based on confidence |
US11204787B2 (en) | 2017-01-09 | 2021-12-21 | Apple Inc. | Application integration with a digital assistant |
US11217251B2 (en) | 2019-05-06 | 2022-01-04 | Apple Inc. | Spoken notifications |
US11227589B2 (en) | 2016-06-06 | 2022-01-18 | Apple Inc. | Intelligent list reading |
US11231904B2 (en) | 2015-03-06 | 2022-01-25 | Apple Inc. | Reducing response latency of intelligent automated assistants |
US11237797B2 (en) | 2019-05-31 | 2022-02-01 | Apple Inc. | User activity shortcut suggestions |
US11244267B2 (en) * | 2019-04-26 | 2022-02-08 | Dell Products L.P. | Digital fulfillment product onboarding system |
US11269678B2 (en) | 2012-05-15 | 2022-03-08 | Apple Inc. | Systems and methods for integrating third party services with a digital assistant |
US11281993B2 (en) | 2016-12-05 | 2022-03-22 | Apple Inc. | Model and ensemble compression for metric learning |
US20220093101A1 (en) * | 2020-09-21 | 2022-03-24 | Amazon Technologies, Inc. | Dialog management for multiple users |
US11289073B2 (en) | 2019-05-31 | 2022-03-29 | Apple Inc. | Device text to speech |
US11301477B2 (en) | 2017-05-12 | 2022-04-12 | Apple Inc. | Feedback analysis of a digital assistant |
US11307752B2 (en) | 2019-05-06 | 2022-04-19 | Apple Inc. | User configurable task triggers |
US11314370B2 (en) | 2013-12-06 | 2022-04-26 | Apple Inc. | Method for extracting salient dialog usage from live data |
US20220137917A1 (en) * | 2020-10-30 | 2022-05-05 | Samsung Electronics Co., Ltd. | Method and system for assigning unique voice for electronic device |
US11348573B2 (en) | 2019-03-18 | 2022-05-31 | Apple Inc. | Multimodality in digital assistant systems |
US11350253B2 (en) | 2011-06-03 | 2022-05-31 | Apple Inc. | Active transport based notifications |
US11360641B2 (en) | 2019-06-01 | 2022-06-14 | Apple Inc. | Increasing the relevance of new available information |
US11386266B2 (en) | 2018-06-01 | 2022-07-12 | Apple Inc. | Text correction |
US11388291B2 (en) | 2013-03-14 | 2022-07-12 | Apple Inc. | System and method for processing voicemail |
US11423908B2 (en) | 2019-05-06 | 2022-08-23 | Apple Inc. | Interpreting spoken requests |
US11423886B2 (en) | 2010-01-18 | 2022-08-23 | Apple Inc. | Task flow identification based on user intent |
US11462215B2 (en) | 2018-09-28 | 2022-10-04 | Apple Inc. | Multi-modal inputs for voice commands |
US11468282B2 (en) | 2015-05-15 | 2022-10-11 | Apple Inc. | Virtual assistant in a communication session |
US11467802B2 (en) | 2017-05-11 | 2022-10-11 | Apple Inc. | Maintaining privacy of personal information |
US11475884B2 (en) | 2019-05-06 | 2022-10-18 | Apple Inc. | Reducing digital assistant latency when a language is incorrectly determined |
US11475898B2 (en) | 2018-10-26 | 2022-10-18 | Apple Inc. | Low-latency multi-speaker speech recognition |
US11488406B2 (en) | 2019-09-25 | 2022-11-01 | Apple Inc. | Text detection using global geometry estimators |
US11495218B2 (en) | 2018-06-01 | 2022-11-08 | Apple Inc. | Virtual assistant operation in multi-device environments |
US11496600B2 (en) | 2019-05-31 | 2022-11-08 | Apple Inc. | Remote execution of machine-learned models |
US11501762B2 (en) * | 2020-07-29 | 2022-11-15 | Microsoft Technology Licensing, Llc | Compounding corrective actions and learning in mixed mode dictation |
US11500672B2 (en) | 2015-09-08 | 2022-11-15 | Apple Inc. | Distributed personal assistant |
US11515044B1 (en) * | 2021-12-31 | 2022-11-29 | Ix Innovation Llc | System for administering a qualitative assessment using an automated verbal interface |
US11526368B2 (en) | 2015-11-06 | 2022-12-13 | Apple Inc. | Intelligent automated assistant in a messaging environment |
US11526518B2 (en) | 2017-09-22 | 2022-12-13 | Amazon Technologies, Inc. | Data reporting system and method |
US11532306B2 (en) | 2017-05-16 | 2022-12-20 | Apple Inc. | Detecting a trigger of a digital assistant |
US11551691B1 (en) * | 2017-08-03 | 2023-01-10 | Wells Fargo Bank, N.A. | Adaptive conversation support bot |
US11579699B1 (en) * | 2015-09-07 | 2023-02-14 | Oliver Markus Haynold | Hysteretic multilevel touch control |
US11638059B2 (en) | 2019-01-04 | 2023-04-25 | Apple Inc. | Content playback on multiple devices |
US11657813B2 (en) | 2019-05-31 | 2023-05-23 | Apple Inc. | Voice identification in digital assistant systems |
US11671920B2 (en) | 2007-04-03 | 2023-06-06 | Apple Inc. | Method and system for operating a multifunction portable electronic device using voice-activation |
US11696060B2 (en) | 2020-07-21 | 2023-07-04 | Apple Inc. | User identification using headphones |
US11720614B2 (en) | 2019-09-06 | 2023-08-08 | Tata Consultancy Services Limited | Method and system for generating a response to an unstructured natural language (NL) query |
US11765209B2 (en) | 2020-05-11 | 2023-09-19 | Apple Inc. | Digital assistant hardware abstraction |
US11790914B2 (en) | 2019-06-01 | 2023-10-17 | Apple Inc. | Methods and user interfaces for voice-based control of electronic devices |
US11798547B2 (en) | 2013-03-15 | 2023-10-24 | Apple Inc. | Voice activated device for use with a voice-based digital assistant |
US11809483B2 (en) | 2015-09-08 | 2023-11-07 | Apple Inc. | Intelligent automated assistant for media search and playback |
US11810578B2 (en) | 2020-05-11 | 2023-11-07 | Apple Inc. | Device arbitration for digital assistant-based intercom systems |
US11838734B2 (en) | 2020-07-20 | 2023-12-05 | Apple Inc. | Multi-device audio adjustment coordination |
US11853536B2 (en) | 2015-09-08 | 2023-12-26 | Apple Inc. | Intelligent automated assistant in a media environment |
US11914848B2 (en) | 2020-05-11 | 2024-02-27 | Apple Inc. | Providing relevant data items based on context |
US11924254B2 (en) | 2021-05-03 | 2024-03-05 | Apple Inc. | Digital assistant hardware abstraction |
Families Citing this family (69)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9820039B2 (en) | 2016-02-22 | 2017-11-14 | Sonos, Inc. | Default playback devices |
US9811314B2 (en) | 2016-02-22 | 2017-11-07 | Sonos, Inc. | Metadata exchange involving a networked playback system and a networked microphone system |
US9947316B2 (en) | 2016-02-22 | 2018-04-17 | Sonos, Inc. | Voice control of a media playback system |
US9965247B2 (en) | 2016-02-22 | 2018-05-08 | Sonos, Inc. | Voice controlled media playback system based on user profile |
US10095470B2 (en) | 2016-02-22 | 2018-10-09 | Sonos, Inc. | Audio response playback |
US10264030B2 (en) | 2016-02-22 | 2019-04-16 | Sonos, Inc. | Networked microphone device control |
US9978390B2 (en) | 2016-06-09 | 2018-05-22 | Sonos, Inc. | Dynamic player selection for audio signal processing |
US10152969B2 (en) | 2016-07-15 | 2018-12-11 | Sonos, Inc. | Voice detection by multiple devices |
US10134399B2 (en) | 2016-07-15 | 2018-11-20 | Sonos, Inc. | Contextualization of voice inputs |
US10115400B2 (en) | 2016-08-05 | 2018-10-30 | Sonos, Inc. | Multiple voice services |
US9942678B1 (en) | 2016-09-27 | 2018-04-10 | Sonos, Inc. | Audio playback settings for voice interaction |
US9743204B1 (en) | 2016-09-30 | 2017-08-22 | Sonos, Inc. | Multi-orientation playback device microphones |
US10181323B2 (en) | 2016-10-19 | 2019-01-15 | Sonos, Inc. | Arbitration-based voice recognition |
US11183181B2 (en) | 2017-03-27 | 2021-11-23 | Sonos, Inc. | Systems and methods of multiple voice services |
US10475449B2 (en) | 2017-08-07 | 2019-11-12 | Sonos, Inc. | Wake-word detection suppression |
US10048930B1 (en) | 2017-09-08 | 2018-08-14 | Sonos, Inc. | Dynamic computation of system response volume |
US10719507B2 (en) * | 2017-09-21 | 2020-07-21 | SayMosaic Inc. | System and method for natural language processing |
US10446165B2 (en) | 2017-09-27 | 2019-10-15 | Sonos, Inc. | Robust short-time fourier transform acoustic echo cancellation during audio playback |
US10051366B1 (en) | 2017-09-28 | 2018-08-14 | Sonos, Inc. | Three-dimensional beam forming with a microphone array |
US10621981B2 (en) | 2017-09-28 | 2020-04-14 | Sonos, Inc. | Tone interference cancellation |
US10482868B2 (en) | 2017-09-28 | 2019-11-19 | Sonos, Inc. | Multi-channel acoustic echo cancellation |
US10466962B2 (en) | 2017-09-29 | 2019-11-05 | Sonos, Inc. | Media playback system with voice assistance |
US10880650B2 (en) | 2017-12-10 | 2020-12-29 | Sonos, Inc. | Network microphone devices with automatic do not disturb actuation capabilities |
US10818290B2 (en) | 2017-12-11 | 2020-10-27 | Sonos, Inc. | Home graph |
WO2019152722A1 (en) | 2018-01-31 | 2019-08-08 | Sonos, Inc. | Device designation of playback and network microphone device arrangements |
US11175880B2 (en) | 2018-05-10 | 2021-11-16 | Sonos, Inc. | Systems and methods for voice-assisted media content selection |
US10847178B2 (en) | 2018-05-18 | 2020-11-24 | Sonos, Inc. | Linear filtering for noise-suppressed speech detection |
US10959029B2 (en) | 2018-05-25 | 2021-03-23 | Sonos, Inc. | Determining and adapting to changes in microphone performance of playback devices |
US10681460B2 (en) | 2018-06-28 | 2020-06-09 | Sonos, Inc. | Systems and methods for associating playback devices with voice assistant services |
US10811014B1 (en) * | 2018-06-28 | 2020-10-20 | Amazon Technologies, Inc. | Contact list reconciliation and permissioning |
US11076035B2 (en) | 2018-08-28 | 2021-07-27 | Sonos, Inc. | Do not disturb feature for audio notifications |
US10461710B1 (en) | 2018-08-28 | 2019-10-29 | Sonos, Inc. | Media playback system with maximum volume setting |
US10587430B1 (en) | 2018-09-14 | 2020-03-10 | Sonos, Inc. | Networked devices, systems, and methods for associating playback devices based on sound codes |
US10878811B2 (en) | 2018-09-14 | 2020-12-29 | Sonos, Inc. | Networked devices, systems, and methods for intelligently deactivating wake-word engines |
US11024331B2 (en) | 2018-09-21 | 2021-06-01 | Sonos, Inc. | Voice detection optimization using sound metadata |
US10811015B2 (en) | 2018-09-25 | 2020-10-20 | Sonos, Inc. | Voice detection optimization based on selected voice assistant service |
US11100923B2 (en) | 2018-09-28 | 2021-08-24 | Sonos, Inc. | Systems and methods for selective wake word detection using neural network models |
US10692518B2 (en) | 2018-09-29 | 2020-06-23 | Sonos, Inc. | Linear filtering for noise-suppressed speech detection via multiple network microphone devices |
US11899519B2 (en) | 2018-10-23 | 2024-02-13 | Sonos, Inc. | Multiple stage network microphone device with reduced power consumption and processing load |
EP3654249A1 (en) | 2018-11-15 | 2020-05-20 | Snips | Dilated convolutions and gating for efficient keyword spotting |
US11100925B2 (en) * | 2018-12-06 | 2021-08-24 | Comcast Cable Communications, Llc | Voice command trigger words |
US11183183B2 (en) | 2018-12-07 | 2021-11-23 | Sonos, Inc. | Systems and methods of operating media playback systems having multiple voice assistant services |
US11132989B2 (en) | 2018-12-13 | 2021-09-28 | Sonos, Inc. | Networked microphone devices, systems, and methods of localized arbitration |
US10602268B1 (en) | 2018-12-20 | 2020-03-24 | Sonos, Inc. | Optimization of network microphone devices using noise classification |
US11213946B1 (en) * | 2018-12-27 | 2022-01-04 | X Development Llc | Mitigating reality gap through optimization of simulated hardware parameter(s) of simulated robot |
US10867604B2 (en) | 2019-02-08 | 2020-12-15 | Sonos, Inc. | Devices, systems, and methods for distributed voice processing |
US11315556B2 (en) | 2019-02-08 | 2022-04-26 | Sonos, Inc. | Devices, systems, and methods for distributed voice processing by transmitting sound data associated with a wake word to an appropriate device for identification |
US11120794B2 (en) | 2019-05-03 | 2021-09-14 | Sonos, Inc. | Voice assistant persistence across multiple network microphone devices |
US10586540B1 (en) | 2019-06-12 | 2020-03-10 | Sonos, Inc. | Network microphone device with command keyword conditioning |
US11361756B2 (en) | 2019-06-12 | 2022-06-14 | Sonos, Inc. | Conditional wake word eventing based on environment |
US11200894B2 (en) | 2019-06-12 | 2021-12-14 | Sonos, Inc. | Network microphone device with command keyword eventing |
CN110289016A (en) * | 2019-06-20 | 2019-09-27 | 深圳追一科技有限公司 | A kind of voice quality detecting method, device and electronic equipment based on actual conversation |
US11138969B2 (en) | 2019-07-31 | 2021-10-05 | Sonos, Inc. | Locally distributed keyword detection |
US10871943B1 (en) | 2019-07-31 | 2020-12-22 | Sonos, Inc. | Noise classification for event detection |
US11138975B2 (en) | 2019-07-31 | 2021-10-05 | Sonos, Inc. | Locally distributed keyword detection |
US11189286B2 (en) | 2019-10-22 | 2021-11-30 | Sonos, Inc. | VAS toggle based on device orientation |
US11200900B2 (en) | 2019-12-20 | 2021-12-14 | Sonos, Inc. | Offline voice control |
CN111161717B (en) * | 2019-12-26 | 2022-03-22 | 思必驰科技股份有限公司 | Skill scheduling method and system for voice conversation platform |
US11562740B2 (en) | 2020-01-07 | 2023-01-24 | Sonos, Inc. | Voice verification for media playback |
US11556307B2 (en) | 2020-01-31 | 2023-01-17 | Sonos, Inc. | Local voice data processing |
US11308958B2 (en) | 2020-02-07 | 2022-04-19 | Sonos, Inc. | Localized wakeword verification |
US11727919B2 (en) | 2020-05-20 | 2023-08-15 | Sonos, Inc. | Memory allocation for keyword spotting engines |
US11308962B2 (en) | 2020-05-20 | 2022-04-19 | Sonos, Inc. | Input detection windowing |
US11482224B2 (en) | 2020-05-20 | 2022-10-25 | Sonos, Inc. | Command keywords with input detection windowing |
US11698771B2 (en) | 2020-08-25 | 2023-07-11 | Sonos, Inc. | Vocal guidance engines for playback devices |
US11657814B2 (en) * | 2020-10-08 | 2023-05-23 | Harman International Industries, Incorporated | Techniques for dynamic auditory phrase completion |
US11435876B1 (en) * | 2020-10-23 | 2022-09-06 | Amazon Technologies, Inc. | Techniques for sharing item information from a user interface |
US11551700B2 (en) | 2021-01-25 | 2023-01-10 | Sonos, Inc. | Systems and methods for power-efficient keyword detection |
US11886281B2 (en) | 2021-08-13 | 2024-01-30 | Bank Of America Corporation | Artificial intelligence engine providing automated error resolution |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20120192096A1 (en) * | 2011-01-25 | 2012-07-26 | Research In Motion Limited | Active command line driven user interface |
US20130332168A1 (en) * | 2012-06-08 | 2013-12-12 | Samsung Electronics Co., Ltd. | Voice activated search and control for applications |
US20130347029A1 (en) * | 2012-06-21 | 2013-12-26 | United Video Properties, Inc. | Systems and methods for navigating to content without an advertisement |
US20140040274A1 (en) * | 2012-07-31 | 2014-02-06 | Veveo, Inc. | Disambiguating user intent in conversational interaction system for large corpus information retrieval |
US8676904B2 (en) * | 2008-10-02 | 2014-03-18 | Apple Inc. | Electronic devices with voice command and contextual data processing capabilities |
US8739208B2 (en) * | 2009-02-12 | 2014-05-27 | Digimarc Corporation | Media processing methods and arrangements |
Family Cites Families (2573)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3859005A (en) | 1973-08-13 | 1975-01-07 | Albert L Huebner | Erosion reduction in wet turbines |
US4826405A (en) | 1985-10-15 | 1989-05-02 | Aeroquip Corporation | Fan blade fabrication system |
US8073695B1 (en) | 1992-12-09 | 2011-12-06 | Adrea, LLC | Electronic book with voice emulation features |
US7835989B1 (en) | 1992-12-09 | 2010-11-16 | Discovery Communications, Inc. | Electronic book alternative delivery systems |
US6311157B1 (en) | 1992-12-31 | 2001-10-30 | Apple Computer, Inc. | Assigning meanings to utterances in a speech recognition system |
EP0694854B1 (en) * | 1994-07-28 | 2002-06-05 | International Business Machines Corporation | Improved neural semiconductor chip architectures and neural networks incorporated therein |
US6122482A (en) | 1995-02-22 | 2000-09-19 | Global Communications, Inc. | Satellite broadcast receiving and distribution system |
US5901287A (en) | 1996-04-01 | 1999-05-04 | The Sabre Group Inc. | Information aggregation and synthesization system |
US7113958B1 (en) | 1996-08-12 | 2006-09-26 | Battelle Memorial Institute | Three-dimensional display of document set |
US6199076B1 (en) | 1996-10-02 | 2001-03-06 | James Logan | Audio program player including a dynamic program selection controller |
US7787647B2 (en) | 1997-01-13 | 2010-08-31 | Micro Ear Technology, Inc. | Portable system for programming hearing aids |
US7614008B2 (en) | 2004-07-30 | 2009-11-03 | Apple Inc. | Operation of a computer with touch screen interface |
US8479122B2 (en) | 2004-07-30 | 2013-07-02 | Apple Inc. | Gestures for touch sensitive input devices |
US7663607B2 (en) | 2004-05-06 | 2010-02-16 | Apple Inc. | Multipoint touchscreen |
EP2256605B1 (en) | 1998-01-26 | 2017-12-06 | Apple Inc. | Method and apparatus for integrating manual input |
US7840912B2 (en) | 2006-01-30 | 2010-11-23 | Apple Inc. | Multi-touch gesture dictionary |
US7603684B1 (en) | 1998-05-19 | 2009-10-13 | United Video Properties, Inc. | Program guide system with video-on-demand browsing |
US20070094222A1 (en) | 1998-05-28 | 2007-04-26 | Lawrence Au | Method and system for using voice input for performing network functions |
US7711672B2 (en) | 1998-05-28 | 2010-05-04 | Lawrence Au | Semantic network methods to disambiguate natural language meaning |
CA2345665C (en) | 1998-10-02 | 2011-02-08 | International Business Machines Corporation | Conversational computing via conversational virtual machine |
US6163794A (en) | 1998-10-23 | 2000-12-19 | General Magic | Network system extensible by users |
US6321092B1 (en) | 1998-11-03 | 2001-11-20 | Signal Soft Corporation | Multiple input data management for wireless location-based applications |
US7447637B1 (en) | 1998-12-23 | 2008-11-04 | Eastern Investments, Llc | System and method of processing speech within a graphic user interface |
US8938688B2 (en) | 1998-12-04 | 2015-01-20 | Nuance Communications, Inc. | Contextual prediction of user words and user actions |
US7881936B2 (en) | 1998-12-04 | 2011-02-01 | Tegic Communications, Inc. | Multimodal disambiguation of speech recognition |
US7712053B2 (en) | 1998-12-04 | 2010-05-04 | Tegic Communications, Inc. | Explicit character filtering of ambiguous text entry |
US7679534B2 (en) | 1998-12-04 | 2010-03-16 | Tegic Communications, Inc. | Contextual prediction of user words and user actions |
US6842877B2 (en) | 1998-12-18 | 2005-01-11 | Tangis Corporation | Contextual responses based on automated learning techniques |
GB2347239B (en) | 1999-02-22 | 2003-09-24 | Nokia Mobile Phones Ltd | A communication terminal having a predictive editor application |
US7596606B2 (en) | 1999-03-11 | 2009-09-29 | Codignotto John D | Message publishing system for publishing messages from identified, authorized senders |
US7761296B1 (en) | 1999-04-02 | 2010-07-20 | International Business Machines Corporation | System and method for rescoring N-best hypotheses of an automatic speech recognition system |
US7558381B1 (en) | 1999-04-22 | 2009-07-07 | Agere Systems Inc. | Retrieval of deleted voice messages in voice messaging system |
US7030863B2 (en) | 2000-05-26 | 2006-04-18 | America Online, Incorporated | Virtual keyboard system with automatic correction |
CA2392446C (en) | 1999-05-27 | 2009-07-14 | America Online Incorporated | Keyboard system with automatic correction |
US7821503B2 (en) | 2003-04-09 | 2010-10-26 | Tegic Communications, Inc. | Touch screen and graphical user interface |
WO2000073936A1 (en) | 1999-05-28 | 2000-12-07 | Sehda, Inc. | Phrase-based dialogue modeling with particular application to creating recognition grammars for voice-controlled user interfaces |
US20140098247A1 (en) | 1999-06-04 | 2014-04-10 | Ip Holdings, Inc. | Home Automation And Smart Home Control Using Mobile Devices And Wireless Enabled Electrical Switches |
US8065155B1 (en) | 1999-06-10 | 2011-11-22 | Gazdzinski Robert F | Adaptive advertising apparatus and methods |
US7711565B1 (en) | 1999-06-10 | 2010-05-04 | Gazdzinski Robert F | “Smart” elevator system and method |
AUPQ138199A0 (en) | 1999-07-02 | 1999-07-29 | Telstra R & D Management Pty Ltd | A search system |
US7451177B1 (en) | 1999-08-12 | 2008-11-11 | Avintaquin Capital, Llc | System for and method of implementing a closed loop response architecture for electronic commerce |
US7743188B2 (en) | 1999-08-12 | 2010-06-22 | Palm, Inc. | Method and apparatus for accessing a contacts database and telephone services |
US7925610B2 (en) | 1999-09-22 | 2011-04-12 | Google Inc. | Determining a meaning of a knowledge item using document-based information |
US6789231B1 (en) | 1999-10-05 | 2004-09-07 | Microsoft Corporation | Method and system for providing alternatives for text derived from stochastic input sources |
US7176372B2 (en) | 1999-10-19 | 2007-02-13 | Medialab Solutions Llc | Interactive digital music recorder and player |
US8392188B1 (en) | 1999-11-05 | 2013-03-05 | At&T Intellectual Property Ii, L.P. | Method and system for building a phonotactic model for domain independent speech recognition |
US7725307B2 (en) | 1999-11-12 | 2010-05-25 | Phoenix Solutions, Inc. | Query engine for processing voice based queries including semantic decoding |
US7050977B1 (en) | 1999-11-12 | 2006-05-23 | Phoenix Solutions, Inc. | Speech-enabled server for internet website and method |
US7392185B2 (en) | 1999-11-12 | 2008-06-24 | Phoenix Solutions, Inc. | Speech based learning/training system using semantic decoding |
US9076448B2 (en) | 1999-11-12 | 2015-07-07 | Nuance Communications, Inc. | Distributed real time speech recognition system |
US7337389B1 (en) | 1999-12-07 | 2008-02-26 | Microsoft Corporation | System and method for annotating an electronic document independently of its content |
US7434177B1 (en) | 1999-12-20 | 2008-10-07 | Apple Inc. | User interface for providing consolidation and access |
US8271287B1 (en) | 2000-01-14 | 2012-09-18 | Alcatel Lucent | Voice command remote control system |
GB2360106B (en) | 2000-02-21 | 2004-09-22 | Ac Properties Bv | Ordering playable works |
WO2001067225A2 (en) | 2000-03-06 | 2001-09-13 | Kanisa Inc. | A system and method for providing an intelligent multi-step dialog with a user |
US6757362B1 (en) | 2000-03-06 | 2004-06-29 | Avaya Technology Corp. | Personal virtual assistant |
US8645137B2 (en) | 2000-03-16 | 2014-02-04 | Apple Inc. | Fast, language-independent method for user authentication by voice |
US8024415B2 (en) | 2001-03-16 | 2011-09-20 | Microsoft Corporation | Priorities generation and management |
US7187947B1 (en) | 2000-03-28 | 2007-03-06 | Affinity Labs, Llc | System and method for communicating selected information to an electronic device |
US7478129B1 (en) | 2000-04-18 | 2009-01-13 | Helen Jeanne Chemtob | Method and apparatus for providing group interaction via communications networks |
US7080315B1 (en) | 2000-06-28 | 2006-07-18 | International Business Machines Corporation | Method and apparatus for coupling a visual browser to a voice browser |
US7672952B2 (en) | 2000-07-13 | 2010-03-02 | Novell, Inc. | System and method of semantic correlation of rich content |
US7853664B1 (en) | 2000-07-31 | 2010-12-14 | Landmark Digital Services Llc | Method and system for purchasing pre-recorded music |
AU2001288469A1 (en) * | 2000-08-28 | 2002-03-13 | Emotion, Inc. | Method and apparatus for digital media management, retrieval, and collaboration |
US7218226B2 (en) | 2004-03-01 | 2007-05-15 | Apple Inc. | Acceleration-based theft detection system for portable electronic devices |
US7688306B2 (en) | 2000-10-02 | 2010-03-30 | Apple Inc. | Methods and apparatuses for operating a portable device based on an accelerometer |
WO2002047467A2 (en) * | 2000-10-24 | 2002-06-20 | Singingfish.Com, Inc. | Method of sizing an embedded media player page |
US6915262B2 (en) | 2000-11-30 | 2005-07-05 | Telesector Resources Group, Inc. | Methods and apparatus for performing speech recognition and using speech recognition results |
US7016847B1 (en) | 2000-12-08 | 2006-03-21 | Ben Franklin Patent Holdings L.L.C. | Open architecture for a voice user interface |
US6996778B2 (en) | 2000-12-11 | 2006-02-07 | Microsoft Corporation | User interface for managing multiple network resources |
US7607083B2 (en) | 2000-12-12 | 2009-10-20 | Nec Corporation | Test summarization using relevance measures and latent semantic analysis |
US6973427B2 (en) | 2000-12-26 | 2005-12-06 | Microsoft Corporation | Method for adding phonetic descriptions to a speech recognition lexicon |
US6677932B1 (en) | 2001-01-28 | 2004-01-13 | Finger Works, Inc. | System and method for recognizing touch typing under limited tactile feedback conditions |
US8213910B2 (en) | 2001-02-09 | 2012-07-03 | Harris Technology, Llc | Telephone using a connection network for processing data remotely from the telephone |
US6570557B1 (en) | 2001-02-10 | 2003-05-27 | Finger Works, Inc. | Multi-touch system and method for emulating modifier keys via fingertip chords |
US7171365B2 (en) | 2001-02-16 | 2007-01-30 | International Business Machines Corporation | Tracking time using portable recorders and speech recognition |
US7290039B1 (en) | 2001-02-27 | 2007-10-30 | Microsoft Corporation | Intent based processing |
US7277853B1 (en) | 2001-03-02 | 2007-10-02 | Mindspeed Technologies, Inc. | System and method for a endpoint detection of speech for improved speech recognition in noisy environments |
US7366979B2 (en) | 2001-03-09 | 2008-04-29 | Copernicus Investments, Llc | Method and apparatus for annotating a document |
EP1490790A2 (en) | 2001-03-13 | 2004-12-29 | Intelligate Ltd. | Dynamic natural language understanding |
CA2408625A1 (en) | 2001-03-14 | 2002-09-19 | At&T Corp. | Method for automated sentence planning in a task classification system |
US7209880B1 (en) | 2001-03-20 | 2007-04-24 | At&T Corp. | Systems and methods for dynamic re-configurable speech recognition |
JP2002358092A (en) | 2001-06-01 | 2002-12-13 | Sony Corp | Voice synthesizing system |
US20020194003A1 (en) | 2001-06-05 | 2002-12-19 | Mozer Todd F. | Client-server security system and method |
US8831949B1 (en) | 2001-06-28 | 2014-09-09 | At&T Intellectual Property I, L.P. | Voice recognition for performing authentication and completing transactions in a systems interface to legacy systems |
US7606712B1 (en) | 2001-06-28 | 2009-10-20 | At&T Intellectual Property Ii, L.P. | Speech recognition interface for voice actuation of legacy systems |
US20050134578A1 (en) | 2001-07-13 | 2005-06-23 | Universal Electronics Inc. | System and methods for interacting with a control environment |
US7987151B2 (en) | 2001-08-10 | 2011-07-26 | General Dynamics Advanced Info Systems, Inc. | Apparatus and method for problem solving using intelligent agents |
US7920682B2 (en) | 2001-08-21 | 2011-04-05 | Byrne William J | Dynamic interactive voice interface |
US7774388B1 (en) | 2001-08-31 | 2010-08-10 | Margaret Runchey | Model of everything with UR-URL combination identity-identifier-addressing-indexing method, means, and apparatus |
EP1457864A1 (en) | 2001-09-21 | 2004-09-15 | International Business Machines Corporation | INPUT APPARATUS, COMPUTER APPARATUS, METHOD FOR IDENTIFYING INPUT OBJECT, METHOD FOR IDENTIFYING INPUT OBJECT IN KEYBOARD, AND COMPUTER PROGRAM |
US7403938B2 (en) | 2001-09-24 | 2008-07-22 | Iac Search & Media, Inc. | Natural language query processing |
US7324947B2 (en) | 2001-10-03 | 2008-01-29 | Promptu Systems Corporation | Global speech user interface |
ITFI20010199A1 (en) | 2001-10-22 | 2003-04-22 | Riccardo Vieri | SYSTEM AND METHOD TO TRANSFORM TEXTUAL COMMUNICATIONS INTO VOICE AND SEND THEM WITH AN INTERNET CONNECTION TO ANY TELEPHONE SYSTEM |
US7312785B2 (en) | 2001-10-22 | 2007-12-25 | Apple Inc. | Method and apparatus for accelerated scrolling |
US7913185B1 (en) | 2001-10-25 | 2011-03-22 | Adobe Systems Incorporated | Graphical insertion of JavaScript pop-up menus |
US20030101054A1 (en) | 2001-11-27 | 2003-05-29 | Ncc, Llc | Integrated system and method for electronic speech recognition and transcription |
US7483832B2 (en) | 2001-12-10 | 2009-01-27 | At&T Intellectual Property I, L.P. | Method and system for customizing voice translation of text to speech |
US7490039B1 (en) | 2001-12-13 | 2009-02-10 | Cisco Technology, Inc. | Text to speech system and method having interactive spelling capabilities |
US7103542B2 (en) | 2001-12-14 | 2006-09-05 | Ben Franklin Patent Holding Llc | Automatically improving a voice recognition system |
US20030191629A1 (en) * | 2002-02-04 | 2003-10-09 | Shinichi Yoshizawa | Interface apparatus and task control method for assisting in the operation of a device using recognition technology |
US8374879B2 (en) * | 2002-02-04 | 2013-02-12 | Microsoft Corporation | Systems and methods for managing interactions from multiple speech-enabled applications |
US7272377B2 (en) | 2002-02-07 | 2007-09-18 | At&T Corp. | System and method of ubiquitous language translation for wireless devices |
US8249880B2 (en) | 2002-02-14 | 2012-08-21 | Intellisist, Inc. | Real-time display of system instructions |
US7009663B2 (en) | 2003-12-17 | 2006-03-07 | Planar Systems, Inc. | Integrated optical light sensitive active matrix liquid crystal display |
US7221287B2 (en) | 2002-03-05 | 2007-05-22 | Triangle Software Llc | Three-dimensional traffic report |
JP2003295882A (en) | 2002-04-02 | 2003-10-15 | Canon Inc | Text structure for speech synthesis, speech synthesizing method, speech synthesizer and computer program therefor |
US7707221B1 (en) | 2002-04-03 | 2010-04-27 | Yahoo! Inc. | Associating and linking compact disc metadata |
US7043474B2 (en) | 2002-04-15 | 2006-05-09 | International Business Machines Corporation | System and method for measuring image similarity based on semantic meaning |
US7869998B1 (en) | 2002-04-23 | 2011-01-11 | At&T Intellectual Property Ii, L.P. | Voice-enabled dialog system |
US8135115B1 (en) | 2006-11-22 | 2012-03-13 | Securus Technologies, Inc. | System and method for multi-channel recording |
US7490034B2 (en) | 2002-04-30 | 2009-02-10 | Microsoft Corporation | Lexicon with sectionalized data and method of using the same |
US7221937B2 (en) | 2002-05-06 | 2007-05-22 | Research In Motion Limited | Event reminder method |
US7493560B1 (en) | 2002-05-20 | 2009-02-17 | Oracle International Corporation | Definition links in online documentation |
US8611919B2 (en) | 2002-05-23 | 2013-12-17 | Wounder Gmbh., Llc | System, method, and computer program product for providing location based services and mobile e-commerce |
US7546382B2 (en) | 2002-05-28 | 2009-06-09 | International Business Machines Corporation | Methods and systems for authoring of mixed-initiative multi-modal interactions and related browsing mechanisms |
US7398209B2 (en) | 2002-06-03 | 2008-07-08 | Voicebox Technologies, Inc. | Systems and methods for responding to natural language speech utterance |
US7680649B2 (en) | 2002-06-17 | 2010-03-16 | International Business Machines Corporation | System, method, program product, and networking use for recognizing words and their parts of speech in one or more natural languages |
US8219608B2 (en) | 2002-06-20 | 2012-07-10 | Koninklijke Philips Electronics N.V. | Scalable architecture for web services |
US7568151B2 (en) | 2002-06-27 | 2009-07-28 | Microsoft Corporation | Notification of activity around documents |
WO2004003887A2 (en) | 2002-06-28 | 2004-01-08 | Conceptual Speech, Llc | Multi-phoneme streamer and knowledge representation speech recognition system and method |
US7079713B2 (en) | 2002-06-28 | 2006-07-18 | Microsoft Corporation | Method and system for displaying and linking ink objects with recognized text and objects |
US7656393B2 (en) | 2005-03-04 | 2010-02-02 | Apple Inc. | Electronic device having display and surrounding touch sensitive bezel for user interface and control |
US7693720B2 (en) | 2002-07-15 | 2010-04-06 | Voicebox Technologies, Inc. | Mobile systems and methods for responding to natural language speech utterance |
US7665024B1 (en) | 2002-07-22 | 2010-02-16 | Verizon Services Corp. | Methods and apparatus for controlling a user interface based on the emotional state of a user |
US6876727B2 (en) | 2002-07-24 | 2005-04-05 | Sbc Properties, Lp | Voice over IP method for developing interactive voice response system |
US7535997B1 (en) | 2002-07-29 | 2009-05-19 | At&T Intellectual Property I, L.P. | Systems and methods for silent message delivery |
US7822687B2 (en) * | 2002-09-16 | 2010-10-26 | Francois Brillon | Jukebox with customizable avatar |
US7027842B2 (en) | 2002-09-24 | 2006-04-11 | Bellsouth Intellectual Property Corporation | Apparatus and method for providing hands-free operation of a device |
US9342829B2 (en) | 2002-10-01 | 2016-05-17 | Andrew H B Zhou | Systems and methods for mobile application, wearable application, transactional messaging, calling, digital multimedia capture and payment transactions |
US8972266B2 (en) | 2002-11-12 | 2015-03-03 | David Bezar | User intent analysis extent of speaker intent analysis system |
US7822611B2 (en) | 2002-11-12 | 2010-10-26 | Bezar David B | Speaker intent analysis system |
US7783486B2 (en) | 2002-11-22 | 2010-08-24 | Roy Jonathan Rosser | Response generator for mimicking human-computer natural language conversation |
US7298930B1 (en) | 2002-11-29 | 2007-11-20 | Ricoh Company, Ltd. | Multimodal access of meeting recordings |
US7684985B2 (en) | 2002-12-10 | 2010-03-23 | Richard Dominach | Techniques for disambiguating speech input using multimodal interfaces |
FR2848688A1 (en) | 2002-12-17 | 2004-06-18 | France Telecom | Text language identifying device for linguistic analysis of text, has analyzing unit to analyze chain characters of words extracted from one text, where each chain is completed so that each time chains are found in word |
US8661112B2 (en) | 2002-12-20 | 2014-02-25 | Nuance Communications, Inc. | Customized interactive voice response menus |
EP1574093B1 (en) | 2002-12-20 | 2009-04-01 | Nokia Corporation | Method and device for organizing user provided information with meta-information |
US7703091B1 (en) | 2002-12-31 | 2010-04-20 | Emc Corporation | Methods and apparatus for installing agents in a managed network |
US7003464B2 (en) | 2003-01-09 | 2006-02-21 | Motorola, Inc. | Dialog recognition and control in a voice browser |
US7593868B2 (en) | 2003-01-29 | 2009-09-22 | Innovation Interactive Llc | Systems and methods for providing contextual advertising information via a communication network |
US7617094B2 (en) | 2003-02-28 | 2009-11-10 | Palo Alto Research Center Incorporated | Methods, apparatus, and products for identifying a conversation |
US7809565B2 (en) | 2003-03-01 | 2010-10-05 | Coifman Robert E | Method and apparatus for improving the transcription accuracy of speech recognition software |
US7805299B2 (en) | 2004-03-01 | 2010-09-28 | Coifman Robert E | Method and apparatus for improving the transcription accuracy of speech recognition software |
US7606790B2 (en) * | 2003-03-03 | 2009-10-20 | Digimarc Corporation | Integrating and enhancing searching of media content and biometric databases |
US7529671B2 (en) | 2003-03-04 | 2009-05-05 | Microsoft Corporation | Block synchronous decoding |
US8064753B2 (en) | 2003-03-05 | 2011-11-22 | Freeman Alan D | Multi-feature media article and method for manufacture of same |
JP4828091B2 (en) | 2003-03-05 | 2011-11-30 | ヒューレット・パッカード・カンパニー | Clustering method program and apparatus |
US7835504B1 (en) | 2003-03-16 | 2010-11-16 | Palm, Inc. | Telephone number parsing and linking |
US8244712B2 (en) | 2003-03-18 | 2012-08-14 | Apple Inc. | Localized viewing of file system names |
US7613797B2 (en) | 2003-03-19 | 2009-11-03 | Unisys Corporation | Remote discovery and system architecture |
US7496498B2 (en) | 2003-03-24 | 2009-02-24 | Microsoft Corporation | Front-end architecture for a multi-lingual text-to-speech system |
US8745541B2 (en) | 2003-03-25 | 2014-06-03 | Microsoft Corporation | Architecture for controlling a computer using hand gestures |
US7941009B2 (en) | 2003-04-08 | 2011-05-10 | The Penn State Research Foundation | Real-time computerized annotation of pictures |
US8224757B2 (en) | 2003-04-15 | 2012-07-17 | Sap Ag | Curriculum management system |
US7711550B1 (en) | 2003-04-29 | 2010-05-04 | Microsoft Corporation | Methods and system for recognizing names in a computer-generated document and for providing helpful actions associated with recognized names |
US7669134B1 (en) | 2003-05-02 | 2010-02-23 | Apple Inc. | Method and apparatus for displaying information during an instant messaging session |
US7407384B2 (en) | 2003-05-29 | 2008-08-05 | Robert Bosch Gmbh | System, method and device for language education through a voice portal server |
US7493251B2 (en) | 2003-05-30 | 2009-02-17 | Microsoft Corporation | Using source-channel models for word segmentation |
US7496230B2 (en) | 2003-06-05 | 2009-02-24 | International Business Machines Corporation | System and method for automatic natural language translation of embedded text regions in images during information transfer |
US7778432B2 (en) | 2003-06-06 | 2010-08-17 | Gn Resound A/S | Hearing aid wireless network |
US7720683B1 (en) | 2003-06-13 | 2010-05-18 | Sensory, Inc. | Method and apparatus of specifying and performing speech recognition operations |
KR100634496B1 (en) | 2003-06-16 | 2006-10-13 | 삼성전자주식회사 | Input language recognition method and apparatus and method and apparatus for automatically interchanging input language modes employing the same |
US7559026B2 (en) | 2003-06-20 | 2009-07-07 | Apple Inc. | Video conferencing system having focus control |
US7827047B2 (en) | 2003-06-24 | 2010-11-02 | At&T Intellectual Property I, L.P. | Methods and systems for assisting scheduling with automation |
US7757182B2 (en) | 2003-06-25 | 2010-07-13 | Microsoft Corporation | Taskbar media player |
US7634732B1 (en) | 2003-06-26 | 2009-12-15 | Microsoft Corporation | Persona menu |
US7739588B2 (en) | 2003-06-27 | 2010-06-15 | Microsoft Corporation | Leveraging markup language data for semantically labeling text strings and data and for providing actions based on semantically labeled text strings and data |
US7580551B1 (en) | 2003-06-30 | 2009-08-25 | The Research Foundation Of State University Of Ny | Method and apparatus for analyzing and/or comparing handwritten and/or biometric samples |
AU2003304306A1 (en) | 2003-07-01 | 2005-01-21 | Nokia Corporation | Method and device for operating a user-input area on an electronic display device |
US8373660B2 (en) | 2003-07-14 | 2013-02-12 | Matt Pallakoff | System and method for a portable multimedia client |
KR100811232B1 (en) | 2003-07-18 | 2008-03-07 | 엘지전자 주식회사 | Turn-by-turn navigation system ? next guidance way |
US7757173B2 (en) | 2003-07-18 | 2010-07-13 | Apple Inc. | Voice menu system |
US8311835B2 (en) | 2003-08-29 | 2012-11-13 | Microsoft Corporation | Assisted multi-modal dialogue |
US7475010B2 (en) | 2003-09-03 | 2009-01-06 | Lingospot, Inc. | Adaptive and scalable method for resolving natural language ambiguities |
US20050054381A1 (en) | 2003-09-05 | 2005-03-10 | Samsung Electronics Co., Ltd. | Proactive user interface |
US7475015B2 (en) | 2003-09-05 | 2009-01-06 | International Business Machines Corporation | Semantic language modeling and confidence measurement |
US7539619B1 (en) | 2003-09-05 | 2009-05-26 | Spoken Translation Ind. | Speech-enabled language translation system and method enabling interactive user supervision of translation and speech recognition accuracy |
AU2003260819A1 (en) | 2003-09-12 | 2005-04-06 | Nokia Corporation | Method and device for handling missed calls in a mobile communications environment |
US7418392B1 (en) | 2003-09-25 | 2008-08-26 | Sensory, Inc. | System and method for controlling the operation of a device by voice commands |
US7386440B2 (en) | 2003-10-01 | 2008-06-10 | International Business Machines Corporation | Method, system, and apparatus for natural language mixed-initiative dialogue processing |
US7548651B2 (en) | 2003-10-03 | 2009-06-16 | Asahi Kasei Kabushiki Kaisha | Data process unit and data process unit control program |
US7620894B1 (en) | 2003-10-08 | 2009-11-17 | Apple Inc. | Automatic, dynamic user interface configuration |
US7487092B2 (en) | 2003-10-17 | 2009-02-03 | International Business Machines Corporation | Interactive debugging and tuning method for CTTS voice building |
US7643990B1 (en) | 2003-10-23 | 2010-01-05 | Apple Inc. | Global boundary-centric feature extraction and associated discontinuity metrics |
US7669177B2 (en) | 2003-10-24 | 2010-02-23 | Microsoft Corporation | System and method for preference application installation and execution |
DE602004021716D1 (en) | 2003-11-12 | 2009-08-06 | Honda Motor Co Ltd | SPEECH RECOGNITION SYSTEM |
US7584092B2 (en) | 2004-11-15 | 2009-09-01 | Microsoft Corporation | Unsupervised learning of paraphrase/translation alternations and selective application thereof |
US7561069B2 (en) | 2003-11-12 | 2009-07-14 | Legalview Assets, Limited | Notification systems and methods enabling a response to change particulars of delivery or pickup |
US7779356B2 (en) | 2003-11-26 | 2010-08-17 | Griesmer James P | Enhanced data tip system and method |
US20090018918A1 (en) | 2004-11-04 | 2009-01-15 | Manyworlds Inc. | Influence-based Social Network Advertising |
DE602004016681D1 (en) | 2003-12-05 | 2008-10-30 | Kenwood Corp | AUDIO DEVICE CONTROL DEVICE, AUDIO DEVICE CONTROL METHOD AND PROGRAM |
US7689412B2 (en) | 2003-12-05 | 2010-03-30 | Microsoft Corporation | Synonymous collocation extraction using translation information |
US7412388B2 (en) | 2003-12-12 | 2008-08-12 | International Business Machines Corporation | Language-enhanced programming tools |
US7427024B1 (en) | 2003-12-17 | 2008-09-23 | Gazdzinski Mark J | Chattel management apparatus and methods |
CN1898721B (en) | 2003-12-26 | 2011-12-07 | 株式会社建伍 | Device control device and method |
US7552055B2 (en) | 2004-01-10 | 2009-06-23 | Microsoft Corporation | Dialog component re-use in recognition systems |
US8160883B2 (en) | 2004-01-10 | 2012-04-17 | Microsoft Corporation | Focus tracking in dialogs |
US8281339B1 (en) | 2004-01-12 | 2012-10-02 | United Video Properties, Inc. | Customizable flip and browse overlays in an interactive television system |
US7660715B1 (en) | 2004-01-12 | 2010-02-09 | Avaya Inc. | Transparent monitoring and intervention to improve automatic adaptation of speech models |
US7707039B2 (en) | 2004-02-15 | 2010-04-27 | Exbiblio B.V. | Automatic modification of web pages |
US8442331B2 (en) * | 2004-02-15 | 2013-05-14 | Google Inc. | Capturing text from rendered documents using supplemental information |
US7610258B2 (en) | 2004-01-30 | 2009-10-27 | Microsoft Corporation | System and method for exposing a child list |
US7542971B2 (en) | 2004-02-02 | 2009-06-02 | Fuji Xerox Co., Ltd. | Systems and methods for collaborative note-taking |
US7596499B2 (en) | 2004-02-02 | 2009-09-29 | Panasonic Corporation | Multilingual text-to-speech system with limited resources |
US7721226B2 (en) | 2004-02-18 | 2010-05-18 | Microsoft Corporation | Glom widget |
US7433876B2 (en) | 2004-02-23 | 2008-10-07 | Radar Networks, Inc. | Semantic web portal and platform |
US8654936B1 (en) | 2004-02-24 | 2014-02-18 | At&T Intellectual Property I, L.P. | Home control, monitoring and communication system using remote voice commands |
KR100462292B1 (en) | 2004-02-26 | 2004-12-17 | 엔에이치엔(주) | A method for providing search results list based on importance information and a system thereof |
US20050195094A1 (en) | 2004-03-05 | 2005-09-08 | White Russell W. | System and method for utilizing a bicycle computer to monitor athletic performance |
US7693715B2 (en) | 2004-03-10 | 2010-04-06 | Microsoft Corporation | Generating large units of graphonemes with mutual information criterion for letter to sound conversion |
US7711129B2 (en) | 2004-03-11 | 2010-05-04 | Apple Inc. | Method and system for approximating graphic equalizers using dynamic filter order reduction |
US7983835B2 (en) | 2004-11-03 | 2011-07-19 | Lagassey Paul J | Modular intelligent transportation system |
US7478033B2 (en) | 2004-03-16 | 2009-01-13 | Google Inc. | Systems and methods for translating Chinese pinyin to Chinese characters |
JP4587160B2 (en) | 2004-03-26 | 2010-11-24 | キヤノン株式会社 | Signal processing apparatus and method |
US7716216B1 (en) | 2004-03-31 | 2010-05-11 | Google Inc. | Document ranking based on semantic distance between terms in a document |
US7747601B2 (en) | 2006-08-14 | 2010-06-29 | Inquira, Inc. | Method and apparatus for identifying and classifying query intent |
US8713418B2 (en) | 2004-04-12 | 2014-04-29 | Google Inc. | Adding value to a rendered document |
US7496512B2 (en) | 2004-04-13 | 2009-02-24 | Microsoft Corporation | Refining of segmental boundaries in speech waveforms using contextual-dependent models |
US7623119B2 (en) | 2004-04-21 | 2009-11-24 | Nokia Corporation | Graphical functions by gestures |
US7657844B2 (en) | 2004-04-30 | 2010-02-02 | International Business Machines Corporation | Providing accessibility compliance within advanced componentry |
JP4296598B2 (en) | 2004-04-30 | 2009-07-15 | カシオ計算機株式会社 | Communication terminal device and communication terminal processing program |
US7447665B2 (en) | 2004-05-10 | 2008-11-04 | Kinetx, Inc. | System and method of self-learning conceptual mapping to organize and interpret data |
US7778830B2 (en) | 2004-05-19 | 2010-08-17 | International Business Machines Corporation | Training speaker-dependent, phrase-based speech grammars using an unsupervised automated technique |
US8130929B2 (en) | 2004-05-25 | 2012-03-06 | Galileo Processing, Inc. | Methods for obtaining complex data in an interactive voice response system |
US7873149B2 (en) | 2004-06-01 | 2011-01-18 | Verizon Business Global Llc | Systems and methods for gathering information |
US8224649B2 (en) | 2004-06-02 | 2012-07-17 | International Business Machines Corporation | Method and apparatus for remote command, control and diagnostics of systems using conversational or audio interface |
US8095364B2 (en) | 2004-06-02 | 2012-01-10 | Tegic Communications, Inc. | Multimodal disambiguation of speech recognition |
US7673340B1 (en) | 2004-06-02 | 2010-03-02 | Clickfox Llc | System and method for analyzing system user behavior |
CA2573002A1 (en) | 2004-06-04 | 2005-12-22 | Benjamin Firooz Ghassabian | Systems to enhance data entry in mobile and fixed environment |
CN1965218A (en) | 2004-06-04 | 2007-05-16 | 皇家飞利浦电子股份有限公司 | Performance prediction for an interactive speech recognition system |
WO2005122145A1 (en) | 2004-06-08 | 2005-12-22 | Metaphor Solutions, Inc. | Speech recognition dialog management |
US7454542B2 (en) | 2004-06-08 | 2008-11-18 | Dartdevices Corporation | System device and method for configuring and operating interoperable device having player and engine |
US7565104B1 (en) | 2004-06-16 | 2009-07-21 | Wendell Brown | Broadcast audio program guide |
US8321786B2 (en) | 2004-06-17 | 2012-11-27 | Apple Inc. | Routine and interface for correcting electronic text |
GB0413743D0 (en) | 2004-06-19 | 2004-07-21 | Ibm | Method and system for approximate string matching |
US20070214133A1 (en) | 2004-06-23 | 2007-09-13 | Edo Liberty | Methods for filtering data and filling in missing data using nonlinear inference |
US8099395B2 (en) | 2004-06-24 | 2012-01-17 | Oracle America, Inc. | System level identity object |
US7720674B2 (en) | 2004-06-29 | 2010-05-18 | Sap Ag | Systems and methods for processing natural language queries |
JP4416643B2 (en) | 2004-06-29 | 2010-02-17 | キヤノン株式会社 | Multimodal input method |
US7505795B1 (en) | 2004-07-07 | 2009-03-17 | Advanced Micro Devices, Inc. | Power save management with customized range for user configuration and tuning value based upon recent usage |
US8589156B2 (en) | 2004-07-12 | 2013-11-19 | Hewlett-Packard Development Company, L.P. | Allocation of speech recognition tasks and combination of results thereof |
US7823123B2 (en) | 2004-07-13 | 2010-10-26 | The Mitre Corporation | Semantic system for integrating software components |
JP4301102B2 (en) | 2004-07-22 | 2009-07-22 | ソニー株式会社 | Audio processing apparatus, audio processing method, program, and recording medium |
US8036893B2 (en) | 2004-07-22 | 2011-10-11 | Nuance Communications, Inc. | Method and system for identifying and correcting accent-induced speech recognition difficulties |
US7936861B2 (en) | 2004-07-23 | 2011-05-03 | At&T Intellectual Property I, L.P. | Announcement system and method of use |
US7603349B1 (en) * | 2004-07-29 | 2009-10-13 | Yahoo! Inc. | User interfaces for search systems using in-line contextual queries |
US7653883B2 (en) | 2004-07-30 | 2010-01-26 | Apple Inc. | Proximity detector in handheld device |
US7725318B2 (en) | 2004-07-30 | 2010-05-25 | Nice Systems Inc. | System and method for improving the accuracy of audio searching |
US8381135B2 (en) | 2004-07-30 | 2013-02-19 | Apple Inc. | Proximity detector in handheld device |
US7831601B2 (en) | 2004-08-04 | 2010-11-09 | International Business Machines Corporation | Method for automatically searching for documents related to calendar and email entries |
US7508324B2 (en) | 2004-08-06 | 2009-03-24 | Daniel Suraqui | Finger activated reduced keyboard and a method for performing text input |
US7724242B2 (en) | 2004-08-06 | 2010-05-25 | Touchtable, Inc. | Touch driven method and apparatus to integrate and display multiple image layers forming alternate depictions of same subject matter |
US7728821B2 (en) | 2004-08-06 | 2010-06-01 | Touchtable, Inc. | Touch detecting interactive display |
JP4563106B2 (en) | 2004-08-09 | 2010-10-13 | アルパイン株式会社 | In-vehicle device and audio output method thereof |
US7869999B2 (en) | 2004-08-11 | 2011-01-11 | Nuance Communications, Inc. | Systems and methods for selecting from multiple phonectic transcriptions for text-to-speech synthesis |
US7895531B2 (en) | 2004-08-16 | 2011-02-22 | Microsoft Corporation | Floating command object |
US8117542B2 (en) | 2004-08-16 | 2012-02-14 | Microsoft Corporation | User interface for displaying selectable software functionality controls that are contextually relevant to a selected object |
US7912699B1 (en) | 2004-08-23 | 2011-03-22 | At&T Intellectual Property Ii, L.P. | System and method of lattice-based search for spoken utterance retrieval |
US20060048055A1 (en) | 2004-08-25 | 2006-03-02 | Jun Wu | Fault-tolerant romanized input method for non-roman characters |
US7853574B2 (en) | 2004-08-26 | 2010-12-14 | International Business Machines Corporation | Method of generating a context-inferenced search query and of sorting a result of the query |
US7477238B2 (en) | 2004-08-31 | 2009-01-13 | Research In Motion Limited | Handheld electronic device with text disambiguation |
US20060059424A1 (en) | 2004-09-15 | 2006-03-16 | Petri Jonah W | Real-time data localization |
US7319385B2 (en) | 2004-09-17 | 2008-01-15 | Nokia Corporation | Sensor data sharing |
US7716056B2 (en) | 2004-09-27 | 2010-05-11 | Robert Bosch Corporation | Method and system for interactive conversational dialogue for cognitively overloaded device users |
US7603381B2 (en) | 2004-09-30 | 2009-10-13 | Microsoft Corporation | Contextual action publishing |
KR100754385B1 (en) | 2004-09-30 | 2007-08-31 | 삼성전자주식회사 | Apparatus and method for object localization, tracking, and separation using audio and video sensors |
US7936863B2 (en) | 2004-09-30 | 2011-05-03 | Avaya Inc. | Method and apparatus for providing communication tasks in a workflow |
US8107401B2 (en) | 2004-09-30 | 2012-01-31 | Avaya Inc. | Method and apparatus for providing a virtual assistant to a communication participant |
US8744852B1 (en) | 2004-10-01 | 2014-06-03 | Apple Inc. | Spoken interfaces |
US7756871B2 (en) | 2004-10-13 | 2010-07-13 | Hewlett-Packard Development Company, L.P. | Article extraction |
US7543232B2 (en) | 2004-10-19 | 2009-06-02 | International Business Machines Corporation | Intelligent web based help system |
US7693719B2 (en) | 2004-10-29 | 2010-04-06 | Microsoft Corporation | Providing personalized voice font for text-to-speech applications |
KR101087483B1 (en) | 2004-11-04 | 2011-11-28 | 엘지전자 주식회사 | Method and apparatus for controlling output of audio signal for route guidance in navigation system |
US7735012B2 (en) | 2004-11-04 | 2010-06-08 | Apple Inc. | Audio user interface for computing devices |
US7885844B1 (en) | 2004-11-16 | 2011-02-08 | Amazon Technologies, Inc. | Automatically generating task recommendations for human task performers |
JP4604178B2 (en) | 2004-11-22 | 2010-12-22 | 独立行政法人産業技術総合研究所 | Speech recognition apparatus and method, and program |
CN101065982B (en) | 2004-11-23 | 2011-06-01 | 诺基亚公司 | Processing a message received from a mobile cellular network |
US7702500B2 (en) | 2004-11-24 | 2010-04-20 | Blaedow Karen R | Method and apparatus for determining the meaning of natural language |
US8498865B1 (en) | 2004-11-30 | 2013-07-30 | Vocera Communications, Inc. | Speech recognition system and method using group call statistics |
JP4297442B2 (en) | 2004-11-30 | 2009-07-15 | 富士通株式会社 | Handwritten information input device |
US7630900B1 (en) | 2004-12-01 | 2009-12-08 | Tellme Networks, Inc. | Method and system for selecting grammars based on geographic information associated with a caller |
US8214214B2 (en) | 2004-12-03 | 2012-07-03 | Phoenix Solutions, Inc. | Emotion detection device and method for use in distributed systems |
US7636657B2 (en) | 2004-12-09 | 2009-12-22 | Microsoft Corporation | Method and apparatus for automatic grammar generation from data entries |
US7853445B2 (en) | 2004-12-10 | 2010-12-14 | Deception Discovery Technologies LLC | Method and system for the automatic recognition of deceptive language |
US20060206330A1 (en) | 2004-12-22 | 2006-09-14 | David Attwater | Mode confidence |
US7818672B2 (en) | 2004-12-30 | 2010-10-19 | Microsoft Corporation | Floating action buttons |
US7987244B1 (en) | 2004-12-30 | 2011-07-26 | At&T Intellectual Property Ii, L.P. | Network repository for voice fonts |
US8478589B2 (en) | 2005-01-05 | 2013-07-02 | At&T Intellectual Property Ii, L.P. | Library of existing spoken dialog data for use in generating new natural language spoken dialog systems |
US7536565B2 (en) | 2005-01-07 | 2009-05-19 | Apple Inc. | Techniques for improved playlist processing on media devices |
US8069422B2 (en) | 2005-01-10 | 2011-11-29 | Samsung Electronics, Co., Ltd. | Contextual task recommendation system and method for determining user's context and suggesting tasks |
US7529677B1 (en) | 2005-01-21 | 2009-05-05 | Itt Manufacturing Enterprises, Inc. | Methods and apparatus for remotely processing locally generated commands to control a local device |
US7873654B2 (en) | 2005-01-24 | 2011-01-18 | The Intellection Group, Inc. | Multimodal natural language query system for processing and analyzing voice and proximity-based queries |
US8150872B2 (en) | 2005-01-24 | 2012-04-03 | The Intellection Group, Inc. | Multimodal natural language query system for processing and analyzing voice and proximity-based queries |
US20070276870A1 (en) * | 2005-01-27 | 2007-11-29 | Outland Research, Llc | Method and apparatus for intelligent media selection using age and/or gender |
US8228299B1 (en) | 2005-01-27 | 2012-07-24 | Singleton Technology, Llc | Transaction automation and archival system using electronic contract and disclosure units |
US7508373B2 (en) | 2005-01-28 | 2009-03-24 | Microsoft Corporation | Form factor and input method for language input |
EP1849099B1 (en) | 2005-02-03 | 2014-05-07 | Apple Inc. | Recommender system for identifying a new set of media items responsive to an input set of media items and knowledge base metrics |
US8200495B2 (en) | 2005-02-04 | 2012-06-12 | Vocollect, Inc. | Methods and systems for considering information about an expected response when performing speech recognition |
US7895039B2 (en) | 2005-02-04 | 2011-02-22 | Vocollect, Inc. | Methods and systems for optimizing model adaptation for a speech recognition system |
US8577683B2 (en) * | 2008-08-15 | 2013-11-05 | Thomas Majchrowski & Associates, Inc. | Multipurpose media players |
US7813481B1 (en) | 2005-02-18 | 2010-10-12 | At&T Mobility Ii Llc | Conversation recording with real-time notification for users of communication terminals |
JP4911028B2 (en) | 2005-02-24 | 2012-04-04 | 富士ゼロックス株式会社 | Word translation device, translation method, and translation program |
US7634413B1 (en) | 2005-02-25 | 2009-12-15 | Apple Inc. | Bitrate constrained variable bitrate audio encoding |
US7676026B1 (en) | 2005-03-08 | 2010-03-09 | Baxtech Asia Pte Ltd | Desktop telephony system |
WO2006095718A1 (en) | 2005-03-10 | 2006-09-14 | Matsushita Electric Industrial Co., Ltd. | Digital broadcast receiving apparatus |
US20060206339A1 (en) * | 2005-03-11 | 2006-09-14 | Silvera Marja M | System and method for voice-enabled media content selection on mobile devices |
JP4404211B2 (en) | 2005-03-14 | 2010-01-27 | 富士ゼロックス株式会社 | Multilingual translation memory, translation method and translation program |
US7706510B2 (en) | 2005-03-16 | 2010-04-27 | Research In Motion | System and method for personalized text-to-voice synthesis |
US7565380B1 (en) | 2005-03-24 | 2009-07-21 | Netlogic Microsystems, Inc. | Memory optimized pattern searching |
US7925525B2 (en) | 2005-03-25 | 2011-04-12 | Microsoft Corporation | Smart reminders |
US8346757B1 (en) | 2005-03-28 | 2013-01-01 | Google Inc. | Determining query terms of little significance |
US7721301B2 (en) | 2005-03-31 | 2010-05-18 | Microsoft Corporation | Processing files from a mobile device using voice commands |
US7664558B2 (en) | 2005-04-01 | 2010-02-16 | Apple Inc. | Efficient techniques for modifying audio playback rates |
EP1866810A1 (en) | 2005-04-04 | 2007-12-19 | MOR(F) Dynamics Pty Ltd | Method for transforming language into a visual form |
GB0507036D0 (en) | 2005-04-07 | 2005-05-11 | Ibm | Method and system for language identification |
GB0507148D0 (en) | 2005-04-08 | 2005-05-18 | Ibm | Method and apparatus for multimodal voice and web services |
US9471566B1 (en) | 2005-04-14 | 2016-10-18 | Oracle America, Inc. | Method and apparatus for converting phonetic language input to written language output |
US7516123B2 (en) | 2005-04-14 | 2009-04-07 | International Business Machines Corporation | Page rank for the semantic web query |
US8260617B2 (en) | 2005-04-18 | 2012-09-04 | Nuance Communications, Inc. | Automating input when testing voice-enabled applications |
US7627481B1 (en) | 2005-04-19 | 2009-12-01 | Apple Inc. | Adapting masking thresholds for encoding a low frequency transient signal in audio data |
US7996589B2 (en) | 2005-04-22 | 2011-08-09 | Microsoft Corporation | Auto-suggest lists and handwritten input |
US7584093B2 (en) | 2005-04-25 | 2009-09-01 | Microsoft Corporation | Method and system for generating spelling suggestions |
US7684990B2 (en) | 2005-04-29 | 2010-03-23 | Nuance Communications, Inc. | Method and apparatus for multiple value confirmation and correction in spoken dialog systems |
ATE476065T1 (en) | 2005-05-03 | 2010-08-15 | Oticon As | SYSTEM AND METHOD FOR SHARING NETWORK RESOURCES BETWEEN HEARING AIDS |
US8046374B1 (en) | 2005-05-06 | 2011-10-25 | Symantec Corporation | Automatic training of a database intrusion detection system |
US7606580B2 (en) | 2005-05-11 | 2009-10-20 | Aol Llc | Personalized location information for mobile devices |
US7886233B2 (en) | 2005-05-23 | 2011-02-08 | Nokia Corporation | Electronic text input involving word completion functionality for predicting word candidates for partial word inputs |
FR2886445A1 (en) | 2005-05-30 | 2006-12-01 | France Telecom | METHOD, DEVICE AND COMPUTER PROGRAM FOR SPEECH RECOGNITION |
US7539882B2 (en) | 2005-05-30 | 2009-05-26 | Rambus Inc. | Self-powered devices and methods |
US8041570B2 (en) | 2005-05-31 | 2011-10-18 | Robert Bosch Corporation | Dialogue management using scripts |
ES2339130T3 (en) | 2005-06-01 | 2010-05-17 | Loquendo S.P.A. | PROCEDURE FOR ADAPTATION OF A NEURAL NETWORK OF AN AUTOMATIC SPEECH RECOGNITION DEVICE. |
US7580576B2 (en) | 2005-06-02 | 2009-08-25 | Microsoft Corporation | Stroke localization and binding to electronic document |
US8024195B2 (en) | 2005-06-27 | 2011-09-20 | Sensory, Inc. | Systems and methods of performing speech recognition using historical information |
US7538685B1 (en) | 2005-06-28 | 2009-05-26 | Avaya Inc. | Use of auditory feedback and audio queues in the realization of a personal virtual assistant |
GB0513225D0 (en) | 2005-06-29 | 2005-08-03 | Ibm | Method and system for building and contracting a linguistic dictionary |
US7542967B2 (en) | 2005-06-30 | 2009-06-02 | Microsoft Corporation | Searching an index of media content |
US7885390B2 (en) | 2005-07-01 | 2011-02-08 | Soleo Communications, Inc. | System and method for multi-modal personal communication services |
US7826945B2 (en) | 2005-07-01 | 2010-11-02 | You Zhang | Automobile speech-recognition interface |
US7881283B2 (en) | 2005-07-13 | 2011-02-01 | Research In Motion Limited | Customizability of event notification on telephony-enabled devices |
US9094636B1 (en) | 2005-07-14 | 2015-07-28 | Zaxcom, Inc. | Systems and methods for remotely controlling local audio devices in a virtual wireless multitrack recording system |
US7912720B1 (en) | 2005-07-20 | 2011-03-22 | At&T Intellectual Property Ii, L.P. | System and method for building emotional machines |
US7809572B2 (en) | 2005-07-20 | 2010-10-05 | Panasonic Corporation | Voice quality change portion locating apparatus |
US7613264B2 (en) | 2005-07-26 | 2009-11-03 | Lsi Corporation | Flexible sampling-rate encoder |
US20090048821A1 (en) | 2005-07-27 | 2009-02-19 | Yahoo! Inc. | Mobile language interpreter with text to speech |
US7571092B1 (en) | 2005-07-29 | 2009-08-04 | Sun Microsystems, Inc. | Method and apparatus for on-demand localization of files |
US7640160B2 (en) | 2005-08-05 | 2009-12-29 | Voicebox Technologies, Inc. | Systems and methods for responding to natural language speech utterance |
US8694322B2 (en) | 2005-08-05 | 2014-04-08 | Microsoft Corporation | Selective confirmation for execution of a voice activated user interface |
US7844037B2 (en) | 2005-08-08 | 2010-11-30 | Palm, Inc. | Method and device for enabling message responses to incoming phone calls |
EP1922717A4 (en) | 2005-08-09 | 2011-03-23 | Mobile Voice Control Llc | Use of multiple speech recognition software instances |
US7620549B2 (en) | 2005-08-10 | 2009-11-17 | Voicebox Technologies, Inc. | System and method of supporting adaptive misrecognition in conversational speech |
KR20080043358A (en) | 2005-08-19 | 2008-05-16 | 그레이스노트 아이엔씨 | Method and system to control operation of a playback device |
US7949529B2 (en) | 2005-08-29 | 2011-05-24 | Voicebox Technologies, Inc. | Mobile systems and methods of supporting natural language human-machine interactions |
US8265939B2 (en) | 2005-08-31 | 2012-09-11 | Nuance Communications, Inc. | Hierarchical methods and apparatus for extracting user intent from spoken utterances |
EP1934971A4 (en) | 2005-08-31 | 2010-10-27 | Voicebox Technologies Inc | Dynamic speech sharpening |
EP1919771A4 (en) | 2005-08-31 | 2010-06-09 | Intuview Itd | Decision-support expert system and methods for real-time exploitation of documents in non-english languages |
US8677377B2 (en) | 2005-09-08 | 2014-03-18 | Apple Inc. | Method and apparatus for building an intelligent automated assistant |
GB2430101A (en) | 2005-09-09 | 2007-03-14 | Mitsubishi Electric Inf Tech | Applying metadata for video navigation |
US8688671B2 (en) | 2005-09-14 | 2014-04-01 | Millennial Media | Managing sponsored content based on geographic region |
US8275399B2 (en) | 2005-09-21 | 2012-09-25 | Buckyball Mobile Inc. | Dynamic context-data tag cloud |
US8270933B2 (en) | 2005-09-26 | 2012-09-18 | Zoomsafer, Inc. | Safety features for portable electronic device |
US7505784B2 (en) | 2005-09-26 | 2009-03-17 | Barbera Melvin A | Safety features for portable electronic device |
US7992085B2 (en) | 2005-09-26 | 2011-08-02 | Microsoft Corporation | Lightweight reference user interface |
US7788590B2 (en) | 2005-09-26 | 2010-08-31 | Microsoft Corporation | Lightweight reference user interface |
US7711562B1 (en) | 2005-09-27 | 2010-05-04 | At&T Intellectual Property Ii, L.P. | System and method for testing a TTS voice |
US9009046B1 (en) | 2005-09-27 | 2015-04-14 | At&T Intellectual Property Ii, L.P. | System and method for disambiguating multiple intents in a natural language dialog system |
US7693716B1 (en) | 2005-09-27 | 2010-04-06 | At&T Intellectual Property Ii, L.P. | System and method of developing a TTS voice |
JP5120826B2 (en) | 2005-09-29 | 2013-01-16 | 独立行政法人産業技術総合研究所 | Pronunciation diagnosis apparatus, pronunciation diagnosis method, recording medium, and pronunciation diagnosis program |
JP4908094B2 (en) | 2005-09-30 | 2012-04-04 | 株式会社リコー | Information processing system, information processing method, and information processing program |
US7633076B2 (en) | 2005-09-30 | 2009-12-15 | Apple Inc. | Automated response to and sensing of user activity in portable devices |
US7577522B2 (en) | 2005-12-05 | 2009-08-18 | Outland Research, Llc | Spatially associated personal reminder system and method |
US7930168B2 (en) | 2005-10-04 | 2011-04-19 | Robert Bosch Gmbh | Natural language processing of disfluent sentences |
CN100483399C (en) | 2005-10-09 | 2009-04-29 | 株式会社东芝 | Training transliteration model, segmentation statistic model and automatic transliterating method and device |
WO2007044806A2 (en) | 2005-10-11 | 2007-04-19 | Aol Llc | Ordering of conversations based on monitored recipient user interaction with corresponding electronic messages |
US8401163B1 (en) | 2005-10-18 | 2013-03-19 | Callwave Communications, Llc | Methods and systems for call processing and for providing call progress status over a network |
US7707032B2 (en) | 2005-10-20 | 2010-04-27 | National Cheng Kung University | Method and system for matching speech data |
WO2007045908A1 (en) | 2005-10-21 | 2007-04-26 | Sfx Technologies Limited | Improvements to audio devices |
US20070094024A1 (en) | 2005-10-22 | 2007-04-26 | International Business Machines Corporation | System and method for improving text input in a shorthand-on-keyboard interface |
US7395959B2 (en) | 2005-10-27 | 2008-07-08 | International Business Machines Corporation | Hands free contact database information entry at a communication device |
US7778632B2 (en) | 2005-10-28 | 2010-08-17 | Microsoft Corporation | Multi-modal device capable of automated actions |
KR100755678B1 (en) | 2005-10-28 | 2007-09-05 | 삼성전자주식회사 | Apparatus and method for detecting named entity |
US9026915B1 (en) | 2005-10-31 | 2015-05-05 | At&T Intellectual Property Ii, L.P. | System and method for creating a presentation using natural language |
US7936339B2 (en) | 2005-11-01 | 2011-05-03 | Leapfrog Enterprises, Inc. | Method and system for invoking computer functionality by interaction with dynamically generated interface regions of a writing surface |
US7640158B2 (en) | 2005-11-08 | 2009-12-29 | Multimodal Technologies, Inc. | Automatic detection and application of editing patterns in draft documents |
US7676463B2 (en) | 2005-11-15 | 2010-03-09 | Kroll Ontrack, Inc. | Information exploration systems and method |
US8042048B2 (en) | 2005-11-17 | 2011-10-18 | Att Knowledge Ventures, L.P. | System and method for home automation |
US7909326B2 (en) | 2005-11-22 | 2011-03-22 | Walker Digital, Llc | Systems, products and processes for conducting instant lottery games |
US20100304342A1 (en) | 2005-11-30 | 2010-12-02 | Linguacomm Enterprises Inc. | Interactive Language Education System and Method |
US8055707B2 (en) | 2005-11-30 | 2011-11-08 | Alcatel Lucent | Calendar interface for digital communications |
GB2433403B (en) | 2005-12-16 | 2009-06-24 | Emil Ltd | A text editing apparatus and method |
DE102005061365A1 (en) | 2005-12-21 | 2007-06-28 | Siemens Ag | Background applications e.g. home banking system, controlling method for use over e.g. user interface, involves associating transactions and transaction parameters over universal dialog specification, and universally operating applications |
US8234494B1 (en) | 2005-12-21 | 2012-07-31 | At&T Intellectual Property Ii, L.P. | Speaker-verification digital signatures |
US7996228B2 (en) | 2005-12-22 | 2011-08-09 | Microsoft Corporation | Voice initiated network operations |
US7657849B2 (en) | 2005-12-23 | 2010-02-02 | Apple Inc. | Unlocking a device by performing gestures on an unlock image |
US7599918B2 (en) | 2005-12-29 | 2009-10-06 | Microsoft Corporation | Dynamic search with implicit user intention mining |
US7685144B1 (en) | 2005-12-29 | 2010-03-23 | Google Inc. | Dynamically autocompleting a data entry |
TWI302265B (en) | 2005-12-30 | 2008-10-21 | High Tech Comp Corp | Moving determination apparatus |
US7890330B2 (en) | 2005-12-30 | 2011-02-15 | Alpine Electronics Inc. | Voice recording tool for creating database used in text to speech synthesis system |
US7684991B2 (en) | 2006-01-05 | 2010-03-23 | Alpine Electronics, Inc. | Digital audio file search method and apparatus using text-to-speech processing |
US7673238B2 (en) | 2006-01-05 | 2010-03-02 | Apple Inc. | Portable media device with video acceleration capabilities |
US8006180B2 (en) | 2006-01-10 | 2011-08-23 | Mircrosoft Corporation | Spell checking in network browser based applications |
JP2007183864A (en) | 2006-01-10 | 2007-07-19 | Fujitsu Ltd | File retrieval method and system therefor |
EP1977312A2 (en) | 2006-01-16 | 2008-10-08 | Zlango Ltd. | Iconic communication |
JP4241736B2 (en) | 2006-01-19 | 2009-03-18 | 株式会社東芝 | Speech processing apparatus and method |
JP2009524357A (en) | 2006-01-20 | 2009-06-25 | カンバーセイショナル コンピューティング コーポレイション | Wearable display interface client device |
FR2896603B1 (en) | 2006-01-20 | 2008-05-02 | Thales Sa | METHOD AND DEVICE FOR EXTRACTING INFORMATION AND TRANSFORMING THEM INTO QUALITATIVE DATA OF A TEXTUAL DOCUMENT |
US9600568B2 (en) | 2006-01-23 | 2017-03-21 | Veritas Technologies Llc | Methods and systems for automatic evaluation of electronic discovery review and productions |
US9275129B2 (en) | 2006-01-23 | 2016-03-01 | Symantec Corporation | Methods and systems to efficiently find similar and near-duplicate emails and files |
US7929805B2 (en) | 2006-01-31 | 2011-04-19 | The Penn State Research Foundation | Image-based CAPTCHA generation system |
IL174107A0 (en) | 2006-02-01 | 2006-08-01 | Grois Dan | Method and system for advertising by means of a search engine over a data network |
US7818291B2 (en) | 2006-02-03 | 2010-10-19 | The General Electric Company | Data object access system and method using dedicated task object |
US8352183B2 (en) | 2006-02-04 | 2013-01-08 | Microsoft Corporation | Maps for social networking and geo blogs |
US7836437B2 (en) | 2006-02-10 | 2010-11-16 | Microsoft Corporation | Semantic annotations for virtual objects |
US20090222270A2 (en) | 2006-02-14 | 2009-09-03 | Ivc Inc. | Voice command interface device |
US9101279B2 (en) | 2006-02-15 | 2015-08-11 | Virtual Video Reality By Ritchey, Llc | Mobile user borne brain activity data and surrounding environment data correlation system |
US7541940B2 (en) | 2006-02-16 | 2009-06-02 | International Business Machines Corporation | Proximity-based task alerts |
US7983910B2 (en) | 2006-03-03 | 2011-07-19 | International Business Machines Corporation | Communicating across voice and text channels with emotion preservation |
KR100764174B1 (en) | 2006-03-03 | 2007-10-08 | 삼성전자주식회사 | Apparatus for providing voice dialogue service and method for operating the apparatus |
US9250703B2 (en) | 2006-03-06 | 2016-02-02 | Sony Computer Entertainment Inc. | Interface with gaze detection and voice input |
US8532678B2 (en) | 2006-03-08 | 2013-09-10 | Tomtom International B.V. | Portable GPS navigation device |
EP1835488B1 (en) | 2006-03-17 | 2008-11-19 | Svox AG | Text to speech synthesis |
US7752152B2 (en) | 2006-03-17 | 2010-07-06 | Microsoft Corporation | Using predictive user models for language modeling on a personal device with user behavior models based on statistical modeling |
DE102006037156A1 (en) | 2006-03-22 | 2007-09-27 | Volkswagen Ag | Interactive operating device and method for operating the interactive operating device |
JP4734155B2 (en) | 2006-03-24 | 2011-07-27 | 株式会社東芝 | Speech recognition apparatus, speech recognition method, and speech recognition program |
US7930183B2 (en) | 2006-03-29 | 2011-04-19 | Microsoft Corporation | Automatic identification of dialog timing problems for an interactive speech dialog application using speech log data indicative of cases of barge-in and timing problems |
US7724696B1 (en) | 2006-03-29 | 2010-05-25 | Amazon Technologies, Inc. | Predictive reader power management |
US8018431B1 (en) | 2006-03-29 | 2011-09-13 | Amazon Technologies, Inc. | Page turner for handheld electronic book reader device |
US20070233806A1 (en) | 2006-03-29 | 2007-10-04 | Mehrzad Asadi | Method and system for conducting an internet search using a mobile radio terminal |
US7283072B1 (en) | 2006-03-30 | 2007-10-16 | International Business Machines Corporation | Methods of creating a dictionary for data compression |
US20090306989A1 (en) | 2006-03-31 | 2009-12-10 | Masayo Kaji | Voice input support device, method thereof, program thereof, recording medium containing the program, and navigation device |
US7756708B2 (en) | 2006-04-03 | 2010-07-13 | Google Inc. | Automatic language model update |
EP2005319B1 (en) | 2006-04-04 | 2017-01-11 | Johnson Controls Technology Company | System and method for extraction of meta data from a digital media storage device for media selection in a vehicle |
US7797629B2 (en) | 2006-04-05 | 2010-09-14 | Research In Motion Limited | Handheld electronic device and method for performing optimized spell checking during text entry by providing a sequentially ordered series of spell-check algorithms |
US8510109B2 (en) | 2007-08-22 | 2013-08-13 | Canyon Ip Holdings Llc | Continuous speech transcription performance indication |
US7996769B2 (en) | 2006-04-05 | 2011-08-09 | Research In Motion Limited | Handheld electronic device and method for performing spell checking during text entry and for providing a spell-check learning feature |
US7777717B2 (en) | 2006-04-05 | 2010-08-17 | Research In Motion Limited | Handheld electronic device and method for performing spell checking during text entry and for integrating the output from such spell checking into the output from disambiguation |
US7693717B2 (en) | 2006-04-12 | 2010-04-06 | Custom Speech Usa, Inc. | Session file modification with annotation using speech recognition or text to speech |
US7707027B2 (en) | 2006-04-13 | 2010-04-27 | Nuance Communications, Inc. | Identification and rejection of meaningless input during natural language classification |
ATE448638T1 (en) | 2006-04-13 | 2009-11-15 | Fraunhofer Ges Forschung | AUDIO SIGNAL DECORRELATOR |
US8046363B2 (en) | 2006-04-13 | 2011-10-25 | Lg Electronics Inc. | System and method for clustering documents |
US8077153B2 (en) | 2006-04-19 | 2011-12-13 | Microsoft Corporation | Precise selection techniques for multi-touch screens |
US7475063B2 (en) | 2006-04-19 | 2009-01-06 | Google Inc. | Augmenting queries with synonyms selected using language statistics |
WO2007127695A2 (en) | 2006-04-25 | 2007-11-08 | Elmo Weber Frank | Prefernce based automatic media summarization |
KR100771626B1 (en) | 2006-04-25 | 2007-10-31 | 엘지전자 주식회사 | Terminal device and method for inputting instructions thereto |
US20070255554A1 (en) | 2006-04-26 | 2007-11-01 | Lucent Technologies Inc. | Language translation service for text message communications |
US8214213B1 (en) | 2006-04-27 | 2012-07-03 | At&T Intellectual Property Ii, L.P. | Speech recognition based on pronunciation modeling |
US7757176B2 (en) | 2006-05-03 | 2010-07-13 | Sanjay Vakil | Method and system for collective calendaring |
US9020804B2 (en) | 2006-05-10 | 2015-04-28 | Xerox Corporation | Method for aligning sentences at the word level enforcing selective contiguity constraints |
JP4969645B2 (en) | 2006-05-10 | 2012-07-04 | コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ | Automatic external defibrillator with voice prompts with enhanced clarity |
WO2007133716A2 (en) | 2006-05-11 | 2007-11-22 | Cerebode, Inc. | Multimodal communication and command control systems and related methods |
WO2007132286A1 (en) | 2006-05-12 | 2007-11-22 | Nokia Corporation | An adaptive user interface |
CN101075228B (en) | 2006-05-15 | 2012-05-23 | 松下电器产业株式会社 | Method and apparatus for named entity recognition in natural language |
US7779353B2 (en) | 2006-05-19 | 2010-08-17 | Microsoft Corporation | Error checking web documents |
US7596765B2 (en) | 2006-05-23 | 2009-09-29 | Sony Ericsson Mobile Communications Ab | Sound feedback on menu navigation |
US7831423B2 (en) | 2006-05-25 | 2010-11-09 | Multimodal Technologies, Inc. | Replacing text representing a concept with an alternate written form of the concept |
US7523108B2 (en) | 2006-06-07 | 2009-04-21 | Platformation, Inc. | Methods and apparatus for searching with awareness of geography and languages |
US20100257160A1 (en) | 2006-06-07 | 2010-10-07 | Yu Cao | Methods & apparatus for searching with awareness of different types of information |
US7483894B2 (en) | 2006-06-07 | 2009-01-27 | Platformation Technologies, Inc | Methods and apparatus for entity search |
US7853577B2 (en) | 2006-06-09 | 2010-12-14 | Ebay Inc. | Shopping context engine |
US7774202B2 (en) | 2006-06-12 | 2010-08-10 | Lockheed Martin Corporation | Speech activated control system and related methods |
US8332218B2 (en) | 2006-06-13 | 2012-12-11 | Nuance Communications, Inc. | Context-based grammars for automated speech recognition |
US20110077943A1 (en) | 2006-06-26 | 2011-03-31 | Nec Corporation | System for generating language model, method of generating language model, and program for language model generation |
US7548895B2 (en) | 2006-06-30 | 2009-06-16 | Microsoft Corporation | Communication-prompted user assistance |
US8279171B2 (en) | 2006-07-06 | 2012-10-02 | Panasonic Corporation | Voice input device |
US8050500B1 (en) | 2006-07-06 | 2011-11-01 | Senapps, LLC | Recognition method and system |
US20080010387A1 (en) | 2006-07-07 | 2008-01-10 | Bryce Allen Curtis | Method for defining a Wiki page layout using a Wiki page |
US7756710B2 (en) | 2006-07-13 | 2010-07-13 | Sri International | Method and apparatus for error correction in speech recognition applications |
US20080022208A1 (en) * | 2006-07-18 | 2008-01-24 | Creative Technology Ltd | System and method for personalizing the user interface of audio rendering devices |
US7796980B1 (en) | 2006-08-11 | 2010-09-14 | Sprint Communications Company L.P. | Remote mobile voice control of digital/personal video recorder |
US7646296B2 (en) | 2006-08-11 | 2010-01-12 | Honda Motor Co., Ltd. | Method and system for receiving and sending navigational data via a wireless messaging service on a navigation system |
US8134481B2 (en) | 2006-08-11 | 2012-03-13 | Honda Motor Co., Ltd. | Method and system for receiving and sending navigational data via a wireless messaging service on a navigation system |
KR100753838B1 (en) | 2006-08-11 | 2007-08-31 | 한국전자통신연구원 | Method and apparatus for supporting a adaptive driving |
WO2008026197A2 (en) | 2006-08-28 | 2008-03-06 | Mark Heifets | System, method and end-user device for vocal delivery of textual data |
US8255206B2 (en) | 2006-08-30 | 2012-08-28 | Nec Corporation | Voice mixing method and multipoint conference server and program using the same method |
US9071701B2 (en) | 2006-08-31 | 2015-06-30 | Qualcomm Incorporated | Using wireless characteristic to trigger generation of position fix |
US7689408B2 (en) | 2006-09-01 | 2010-03-30 | Microsoft Corporation | Identifying language of origin for words using estimates of normalized appearance frequency |
US7683886B2 (en) | 2006-09-05 | 2010-03-23 | Research In Motion Limited | Disambiguated text message review function |
US8170790B2 (en) | 2006-09-05 | 2012-05-01 | Garmin Switzerland Gmbh | Apparatus for switching navigation device mode |
US7996792B2 (en) | 2006-09-06 | 2011-08-09 | Apple Inc. | Voicemail manager for portable multifunction device |
US8564544B2 (en) | 2006-09-06 | 2013-10-22 | Apple Inc. | Touch screen device, method, and graphical user interface for customizing display of content category icons |
US8589869B2 (en) | 2006-09-07 | 2013-11-19 | Wolfram Alpha Llc | Methods and systems for determining a formula |
TWI322610B (en) | 2006-09-08 | 2010-03-21 | Htc Corp | Handheld electronic device |
US9318108B2 (en) | 2010-01-18 | 2016-04-19 | Apple Inc. | Intelligent automated assistant |
US9892650B2 (en) | 2006-09-11 | 2018-02-13 | Houghton Mifflin Harcourt Publishing Company | Recovery of polled data after an online test platform failure |
WO2008031625A2 (en) | 2006-09-15 | 2008-03-20 | Exbiblio B.V. | Capture and display of annotations in paper and electronic documents |
WO2008033095A1 (en) | 2006-09-15 | 2008-03-20 | Agency For Science, Technology And Research | Apparatus and method for speech utterance verification |
KR100813170B1 (en) | 2006-09-27 | 2008-03-17 | 삼성전자주식회사 | Method and system for semantic event indexing by analyzing user annotation of digital photos |
US7930197B2 (en) | 2006-09-28 | 2011-04-19 | Microsoft Corporation | Personal data mining |
US7649454B2 (en) | 2006-09-28 | 2010-01-19 | Ektimisi Semiotics Holdings, Llc | System and method for providing a task reminder based on historical travel information |
US8214208B2 (en) | 2006-09-28 | 2012-07-03 | Reqall, Inc. | Method and system for sharing portable voice profiles |
US7528713B2 (en) | 2006-09-28 | 2009-05-05 | Ektimisi Semiotics Holdings, Llc | Apparatus and method for providing a task reminder based on travel history |
US8014308B2 (en) | 2006-09-28 | 2011-09-06 | Microsoft Corporation | Hardware architecture for cloud services |
US7945470B1 (en) | 2006-09-29 | 2011-05-17 | Amazon Technologies, Inc. | Facilitating performance of submitted tasks by mobile task performers |
US7831432B2 (en) | 2006-09-29 | 2010-11-09 | International Business Machines Corporation | Audio menus describing media contents of media players |
DE602006005055D1 (en) | 2006-10-02 | 2009-03-19 | Harman Becker Automotive Sys | Use of language identification of media file data in speech dialogue systems |
JP2008092269A (en) | 2006-10-02 | 2008-04-17 | Matsushita Electric Ind Co Ltd | Hands-free communication device |
US7673251B1 (en) | 2006-10-02 | 2010-03-02 | Adobe Systems, Incorporated | Panel presentation |
US7801721B2 (en) | 2006-10-02 | 2010-09-21 | Google Inc. | Displaying original text in a user interface with translated text |
JP2008096541A (en) | 2006-10-06 | 2008-04-24 | Canon Inc | Speech processing device and control method therefor |
US7937075B2 (en) | 2006-10-06 | 2011-05-03 | At&T Intellectual Property I, L.P. | Mode changing of a mobile communications device and vehicle settings when the mobile communications device is in proximity to a vehicle |
US8145473B2 (en) | 2006-10-10 | 2012-03-27 | Abbyy Software Ltd. | Deep model statistics method for machine translation |
US20100278391A1 (en) | 2006-10-12 | 2010-11-04 | Yung-Tai Hsu | Apparatus for behavior analysis and method thereof |
US8073681B2 (en) | 2006-10-16 | 2011-12-06 | Voicebox Technologies, Inc. | System and method for a cooperative conversational voice user interface |
US7681126B2 (en) | 2006-10-24 | 2010-03-16 | Edgetech America, Inc. | Method for spell-checking location-bound words within a document |
US8972268B2 (en) | 2008-04-15 | 2015-03-03 | Facebook, Inc. | Enhanced speech-to-speech translation system and methods for adding a new word |
US8255216B2 (en) | 2006-10-30 | 2012-08-28 | Nuance Communications, Inc. | Speech recognition of character sequences |
US9471333B2 (en) | 2006-11-03 | 2016-10-18 | Conceptual Speech, Llc | Contextual speech-recognition user-interface driven system and method |
US9355568B2 (en) | 2006-11-13 | 2016-05-31 | Joyce S. Stone | Systems and methods for providing an electronic reader having interactive and educational features |
CN101193460B (en) | 2006-11-20 | 2011-09-28 | 松下电器产业株式会社 | Sound detection device and method |
US8055502B2 (en) | 2006-11-28 | 2011-11-08 | General Motors Llc | Voice dialing using a rejection reference |
US8401847B2 (en) | 2006-11-30 | 2013-03-19 | National Institute Of Advanced Industrial Science And Technology | Speech recognition system and program therefor |
GB0623915D0 (en) | 2006-11-30 | 2007-01-10 | Ibm | Phonetic decoding and concatentive speech synthesis |
US9830912B2 (en) | 2006-11-30 | 2017-11-28 | Ashwin P Rao | Speak and touch auto correction interface |
US8571862B2 (en) | 2006-11-30 | 2013-10-29 | Ashwin P. Rao | Multimodal interface for input of text |
US7831246B1 (en) | 2006-12-08 | 2010-11-09 | At&T Mobility Ii, Llc | Mobile merchant |
US8032510B2 (en) | 2008-03-03 | 2011-10-04 | Yahoo! Inc. | Social aspects of content aggregation, syndication, sharing, and updating |
EP2103178A1 (en) | 2006-12-13 | 2009-09-23 | Phonak AG | Method and system for hearing device fitting |
US8731610B2 (en) | 2006-12-13 | 2014-05-20 | Samsung Electronics Co., Ltd. | Method for adaptive user interface in mobile devices |
US7783644B1 (en) | 2006-12-13 | 2010-08-24 | Google Inc. | Query-independent entity importance in books |
US7646297B2 (en) | 2006-12-15 | 2010-01-12 | At&T Intellectual Property I, L.P. | Context-detected auto-mode switching |
US7552045B2 (en) | 2006-12-18 | 2009-06-23 | Nokia Corporation | Method, apparatus and computer program product for providing flexible text based language identification |
US8447589B2 (en) | 2006-12-22 | 2013-05-21 | Nec Corporation | Text paraphrasing method and program, conversion rule computing method and program, and text paraphrasing system |
US7865817B2 (en) | 2006-12-29 | 2011-01-04 | Amazon Technologies, Inc. | Invariant referencing in digital works |
US8019271B1 (en) | 2006-12-29 | 2011-09-13 | Nextel Communications, Inc. | Methods and systems for presenting information on mobile devices |
US7889184B2 (en) | 2007-01-05 | 2011-02-15 | Apple Inc. | Method, system and graphical user interface for displaying hyperlink information |
EP2099652B1 (en) | 2007-01-05 | 2016-11-16 | Visteon Global Technologies, Inc. | System and method for customized audio prompting |
US7889185B2 (en) | 2007-01-05 | 2011-02-15 | Apple Inc. | Method, system, and graphical user interface for activating hyperlinks |
US8060824B2 (en) | 2007-01-05 | 2011-11-15 | Starz Entertainment Llc | User interface for a multimedia service |
US8391844B2 (en) | 2007-01-07 | 2013-03-05 | Apple Inc. | Voicemail systems and methods |
EP2119205A2 (en) | 2007-01-09 | 2009-11-18 | Spinvox Limited | Detection of unanswered call in order to give calling party the option to alternatively dictate a text message for delivery to the called party |
US8056070B2 (en) | 2007-01-10 | 2011-11-08 | Goller Michael D | System and method for modifying and updating a speech recognition program |
US7912724B1 (en) | 2007-01-18 | 2011-03-22 | Adobe Systems Incorporated | Audio comparison using phoneme matching |
KR100837166B1 (en) | 2007-01-20 | 2008-06-11 | 엘지전자 주식회사 | Method of displaying an information in electronic device and the electronic device thereof |
US9524355B2 (en) | 2007-01-22 | 2016-12-20 | Mozy, Inc. | Methods for delivering task-related digital content based on task-oriented user activity |
US7707226B1 (en) | 2007-01-29 | 2010-04-27 | Aol Inc. | Presentation of content items based on dynamic monitoring of real-time context |
JP2008185805A (en) | 2007-01-30 | 2008-08-14 | Internatl Business Mach Corp <Ibm> | Technology for creating high quality synthesis voice |
US20080186196A1 (en) | 2007-02-01 | 2008-08-07 | Sony Ericsson Mobile Communications Ab | Non-time based snooze |
US7818176B2 (en) | 2007-02-06 | 2010-10-19 | Voicebox Technologies, Inc. | System and method for selecting and presenting advertisements based on natural language processing of voice-based input |
EP2126900B1 (en) | 2007-02-06 | 2013-04-24 | Nuance Communications Austria GmbH | Method and system for creating entries in a speech recognition lexicon |
WO2008098029A1 (en) | 2007-02-06 | 2008-08-14 | Vidoop, Llc. | System and method for authenticating a user to a computer system |
US20080195630A1 (en) | 2007-02-13 | 2008-08-14 | Amadeus S.A.S. | Web service interrogation method and apparatus |
US8078978B2 (en) | 2007-10-19 | 2011-12-13 | Google Inc. | Method and system for predicting text |
US7912828B2 (en) | 2007-02-23 | 2011-03-22 | Apple Inc. | Pattern searching methods and apparatuses |
US7801728B2 (en) | 2007-02-26 | 2010-09-21 | Nuance Communications, Inc. | Document session replay for multimodal applications |
US7797265B2 (en) | 2007-02-26 | 2010-09-14 | Siemens Corporation | Document clustering that applies a locality sensitive hashing function to a feature vector to obtain a limited set of candidate clusters |
US7822608B2 (en) | 2007-02-27 | 2010-10-26 | Nuance Communications, Inc. | Disambiguating a speech recognition grammar in a multimodal application |
US7826872B2 (en) | 2007-02-28 | 2010-11-02 | Sony Ericsson Mobile Communications Ab | Audio nickname tag associated with PTT user |
EP2135231A4 (en) | 2007-03-01 | 2014-10-15 | Adapx Inc | System and method for dynamic learning |
US8362642B2 (en) | 2007-03-01 | 2013-01-29 | Rambus Inc. | Optimized power supply for an electronic system |
JP5511372B2 (en) | 2007-03-02 | 2014-06-04 | パナソニック株式会社 | Adaptive excitation vector quantization apparatus and adaptive excitation vector quantization method |
US8886540B2 (en) | 2007-03-07 | 2014-11-11 | Vlingo Corporation | Using speech recognition results based on an unstructured language model in a mobile communication facility application |
US20110054894A1 (en) | 2007-03-07 | 2011-03-03 | Phillips Michael S | Speech recognition through the collection of contact information in mobile dictation application |
US8838457B2 (en) | 2007-03-07 | 2014-09-16 | Vlingo Corporation | Using results of unstructured language model based speech recognition to control a system-level function of a mobile communications facility |
US8996379B2 (en) | 2007-03-07 | 2015-03-31 | Vlingo Corporation | Speech recognition text entry for software applications |
US8886545B2 (en) | 2007-03-07 | 2014-11-11 | Vlingo Corporation | Dealing with switch latency in speech recognition |
US8635243B2 (en) | 2007-03-07 | 2014-01-21 | Research In Motion Limited | Sending a communications header with voice recording to send metadata for use in speech recognition, formatting, and search mobile search application |
US20090030685A1 (en) | 2007-03-07 | 2009-01-29 | Cerra Joseph P | Using speech recognition results based on an unstructured language model with a navigation system |
US20110060587A1 (en) | 2007-03-07 | 2011-03-10 | Phillips Michael S | Command and control utilizing ancillary information in a mobile voice-to-speech application |
US8949266B2 (en) | 2007-03-07 | 2015-02-03 | Vlingo Corporation | Multiple web-based content category searching in mobile search application |
SE530911C2 (en) | 2007-03-07 | 2008-10-14 | Hexaformer Ab | Transformer arrangement |
US7801729B2 (en) | 2007-03-13 | 2010-09-21 | Sensory, Inc. | Using multiple attributes to create a voice search playlist |
JP4466666B2 (en) | 2007-03-14 | 2010-05-26 | 日本電気株式会社 | Minutes creation method, apparatus and program thereof |
US8219406B2 (en) | 2007-03-15 | 2012-07-10 | Microsoft Corporation | Speech-centric multimodal user interface design in mobile technology |
WO2008114448A1 (en) | 2007-03-20 | 2008-09-25 | Fujitsu Limited | Speech recognition system, speech recognition program, and speech recognition method |
US8714987B2 (en) | 2007-03-28 | 2014-05-06 | Breakthrough Performancetech, Llc | Systems and methods for computerized interactive training |
US7797269B2 (en) | 2007-03-29 | 2010-09-14 | Nokia Corporation | Method and apparatus using a context sensitive dictionary |
CN101542592A (en) | 2007-03-29 | 2009-09-23 | 松下电器产业株式会社 | Keyword extracting device |
US8775931B2 (en) | 2007-03-30 | 2014-07-08 | Blackberry Limited | Spell check function that applies a preference to a spell check algorithm based upon extensive user selection of spell check results generated by the algorithm, and associated handheld electronic device |
US8977255B2 (en) * | 2007-04-03 | 2015-03-10 | Apple Inc. | Method and system for operating a multi-function portable electronic device using voice-activation |
US7920902B2 (en) | 2007-04-04 | 2011-04-05 | Carroll David W | Mobile personal audio device |
US7809610B2 (en) | 2007-04-09 | 2010-10-05 | Platformation, Inc. | Methods and apparatus for freshness and completeness of information |
CN105117376B (en) | 2007-04-10 | 2018-07-10 | 谷歌有限责任公司 | Multi-mode input method editor |
DK1981253T3 (en) | 2007-04-10 | 2011-10-03 | Oticon As | User interfaces for a communication device |
WO2008125107A1 (en) | 2007-04-16 | 2008-10-23 | Gn Resound A/S | A hearing aid wireless communication adaptor |
JP4412504B2 (en) | 2007-04-17 | 2010-02-10 | 本田技研工業株式会社 | Speech recognition apparatus, speech recognition method, and speech recognition program |
US7848924B2 (en) | 2007-04-17 | 2010-12-07 | Nokia Corporation | Method, apparatus and computer program product for providing voice conversion using temporal dynamic features |
US8695074B2 (en) | 2007-04-26 | 2014-04-08 | Microsoft Corporation | Pre-authenticated calling for voice applications |
US7983915B2 (en) | 2007-04-30 | 2011-07-19 | Sonic Foundry, Inc. | Audio content search engine |
US8005664B2 (en) | 2007-04-30 | 2011-08-23 | Tachyon Technologies Pvt. Ltd. | System, method to generate transliteration and method for generating decision tree to obtain transliteration |
US7912289B2 (en) | 2007-05-01 | 2011-03-22 | Microsoft Corporation | Image text replacement |
US8032383B1 (en) | 2007-05-04 | 2011-10-04 | Foneweb, Inc. | Speech controlled services and devices using internet |
US7899666B2 (en) | 2007-05-04 | 2011-03-01 | Expert System S.P.A. | Method and system for automatically extracting relations between concepts included in text |
KR20090001716A (en) | 2007-05-14 | 2009-01-09 | 이병수 | System for operating of growing intelligence form cyber secretary and method thereof |
US8538757B2 (en) | 2007-05-17 | 2013-09-17 | Redstart Systems, Inc. | System and method of a list commands utility for a speech recognition command system |
US8886521B2 (en) | 2007-05-17 | 2014-11-11 | Redstart Systems, Inc. | System and method of dictation for a speech recognition command system |
US8700005B1 (en) | 2007-05-21 | 2014-04-15 | Amazon Technologies, Inc. | Notification of a user device to perform an action |
EG25474A (en) | 2007-05-21 | 2012-01-11 | Sherikat Link Letatweer Elbarmaguey At Sae | Method for translitering and suggesting arabic replacement for a given user input |
US20100215195A1 (en) * | 2007-05-22 | 2010-08-26 | Koninklijke Philips Electronics N.V. | Device for and a method of processing audio data |
US8099418B2 (en) | 2007-05-28 | 2012-01-17 | Panasonic Corporation | Information search support method and information search support device |
US20090027334A1 (en) | 2007-06-01 | 2009-01-29 | Cybernet Systems Corporation | Method for controlling a graphical user interface for touchscreen-enabled computer systems |
US8055708B2 (en) | 2007-06-01 | 2011-11-08 | Microsoft Corporation | Multimedia spaces |
US8204238B2 (en) | 2007-06-08 | 2012-06-19 | Sensory, Inc | Systems and methods of sonic communication |
WO2008151624A1 (en) | 2007-06-13 | 2008-12-18 | Widex A/S | Hearing aid system establishing a conversation group among hearing aids used by different users |
CA2690238A1 (en) | 2007-06-13 | 2008-12-18 | Widex A/S | A system and a method for establishing a conversation group among a number of hearing aids |
JP4970160B2 (en) | 2007-06-22 | 2012-07-04 | アルパイン株式会社 | In-vehicle system and current location mark point guidance method |
US7689421B2 (en) | 2007-06-27 | 2010-03-30 | Microsoft Corporation | Voice persona service for embedding text-to-speech features into software programs |
US8090621B1 (en) | 2007-06-27 | 2012-01-03 | Amazon Technologies, Inc. | Method and system for associating feedback with recommendation rules |
US8763058B2 (en) | 2007-06-28 | 2014-06-24 | Apple Inc. | Selective data downloading and presentation based on user interaction |
US7861008B2 (en) | 2007-06-28 | 2010-12-28 | Apple Inc. | Media management and routing within an electronic device |
US8190627B2 (en) | 2007-06-28 | 2012-05-29 | Microsoft Corporation | Machine assisted query formulation |
US9632561B2 (en) | 2007-06-28 | 2017-04-25 | Apple Inc. | Power-gating media decoders to reduce power consumption |
US8065624B2 (en) | 2007-06-28 | 2011-11-22 | Panasonic Corporation | Virtual keypad systems and methods |
US8260809B2 (en) | 2007-06-28 | 2012-09-04 | Microsoft Corporation | Voice-based search processing |
US8041438B2 (en) | 2007-06-28 | 2011-10-18 | Apple Inc. | Data-driven media management within an electronic device |
US9794605B2 (en) | 2007-06-28 | 2017-10-17 | Apple Inc. | Using time-stamped event entries to facilitate synchronizing data streams |
US7962344B2 (en) | 2007-06-29 | 2011-06-14 | Microsoft Corporation | Depicting a speech user interface via graphical elements |
US8019606B2 (en) | 2007-06-29 | 2011-09-13 | Microsoft Corporation | Identification and selection of a software application via speech |
KR100930802B1 (en) | 2007-06-29 | 2009-12-09 | 엔에이치엔(주) | Browser control method and system using images |
US8290775B2 (en) | 2007-06-29 | 2012-10-16 | Microsoft Corporation | Pronunciation correction of text-to-speech systems between different spoken languages |
JP4424382B2 (en) | 2007-07-04 | 2010-03-03 | ソニー株式会社 | Content reproduction apparatus and content automatic reception method |
US7617074B2 (en) | 2007-07-06 | 2009-11-10 | Microsoft Corporation | Suppressing repeated events and storing diagnostic information |
US8219399B2 (en) | 2007-07-11 | 2012-07-10 | Garmin Switzerland Gmbh | Automated speech recognition (ASR) tiling |
US8306235B2 (en) | 2007-07-17 | 2012-11-06 | Apple Inc. | Method and apparatus for using a sound sensor to adjust the audio output for a device |
DE102007033472A1 (en) | 2007-07-18 | 2009-01-29 | Siemens Ag | Method for speech recognition |
US7890493B2 (en) | 2007-07-20 | 2011-02-15 | Google Inc. | Translating a search query into multiple languages |
CN101354746B (en) | 2007-07-23 | 2011-08-31 | 夏普株式会社 | Device and method for extracting character image |
AU2008201643B1 (en) | 2007-07-24 | 2008-08-28 | Rambrandt Messaging Technologies, LP | Messaging service in a wireless communications network |
ITFI20070177A1 (en) | 2007-07-26 | 2009-01-27 | Riccardo Vieri | SYSTEM FOR THE CREATION AND SETTING OF AN ADVERTISING CAMPAIGN DERIVING FROM THE INSERTION OF ADVERTISING MESSAGES WITHIN AN EXCHANGE OF MESSAGES AND METHOD FOR ITS FUNCTIONING. |
EP2183913A4 (en) | 2007-07-30 | 2011-06-22 | Lg Electronics Inc | Display device and speaker system for the display device |
EP2183685A4 (en) | 2007-08-01 | 2012-08-08 | Ginger Software Inc | Automatic context sensitive language correction and enhancement using an internet corpus |
JP2009036999A (en) | 2007-08-01 | 2009-02-19 | Infocom Corp | Interactive method using computer, interactive system, computer program and computer-readable storage medium |
US9342496B2 (en) | 2007-08-06 | 2016-05-17 | Apple Inc. | Auto-completion of names |
TW200907695A (en) | 2007-08-06 | 2009-02-16 | jian-qiang Peng | System and method of fast opening network link service |
US20090043583A1 (en) | 2007-08-08 | 2009-02-12 | International Business Machines Corporation | Dynamic modification of voice selection based on user specific factors |
US7983919B2 (en) | 2007-08-09 | 2011-07-19 | At&T Intellectual Property Ii, L.P. | System and method for performing speech synthesis with a cache of phoneme sequences |
US7983478B2 (en) | 2007-08-10 | 2011-07-19 | Microsoft Corporation | Hidden markov model based handwriting/calligraphy generation |
US8321222B2 (en) | 2007-08-14 | 2012-11-27 | Nuance Communications, Inc. | Synthesis by generation and concatenation of multi-form segments |
JP2009048245A (en) | 2007-08-14 | 2009-03-05 | Konami Digital Entertainment:Kk | Input reception device, area control method and program |
US8478598B2 (en) | 2007-08-17 | 2013-07-02 | International Business Machines Corporation | Apparatus, system, and method for voice chat transcription |
KR101490687B1 (en) | 2007-08-20 | 2015-02-06 | 삼성전자주식회사 | Method and apparatus for sharing secret information between devices in home network |
JP4987623B2 (en) | 2007-08-20 | 2012-07-25 | 株式会社東芝 | Apparatus and method for interacting with user by voice |
US20090055187A1 (en) | 2007-08-21 | 2009-02-26 | Howard Leventhal | Conversion of text email or SMS message to speech spoken by animated avatar for hands-free reception of email and SMS messages while driving a vehicle |
US8140632B1 (en) | 2007-08-22 | 2012-03-20 | Victor Roditis Jablokov | Facilitating presentation by mobile device of additional content for a word or phrase upon utterance thereof |
US7788276B2 (en) | 2007-08-22 | 2010-08-31 | Yahoo! Inc. | Predictive stemming for web search with statistical machine translation models |
US7917355B2 (en) | 2007-08-23 | 2011-03-29 | Google Inc. | Word detection |
US7983902B2 (en) | 2007-08-23 | 2011-07-19 | Google Inc. | Domain dictionary creation by detection of new topic words using divergence value comparison |
US20090055186A1 (en) | 2007-08-23 | 2009-02-26 | International Business Machines Corporation | Method to voice id tag content to ease reading for visually impaired |
KR101359715B1 (en) | 2007-08-24 | 2014-02-10 | 삼성전자주식회사 | Method and apparatus for providing mobile voice web |
US8126274B2 (en) | 2007-08-30 | 2012-02-28 | Microsoft Corporation | Visual language modeling for image classification |
WO2009029910A2 (en) | 2007-08-31 | 2009-03-05 | Proxpro, Inc. | Situation-aware personal information management for a mobile device |
US8683378B2 (en) | 2007-09-04 | 2014-03-25 | Apple Inc. | Scrolling techniques for user interfaces |
US8683197B2 (en) | 2007-09-04 | 2014-03-25 | Apple Inc. | Method and apparatus for providing seamless resumption of video playback |
US8826132B2 (en) | 2007-09-04 | 2014-09-02 | Apple Inc. | Methods and systems for navigating content on a portable device |
US20090058823A1 (en) | 2007-09-04 | 2009-03-05 | Apple Inc. | Virtual Keyboards in Multi-Language Environment |
US20090106397A1 (en) | 2007-09-05 | 2009-04-23 | O'keefe Sean Patrick | Method and apparatus for interactive content distribution |
US9812023B2 (en) | 2007-09-10 | 2017-11-07 | Excalibur Ip, Llc | Audible metadata |
JP4310371B2 (en) | 2007-09-11 | 2009-08-05 | パナソニック株式会社 | Sound determination device, sound detection device, and sound determination method |
US20090070109A1 (en) | 2007-09-12 | 2009-03-12 | Microsoft Corporation | Speech-to-Text Transcription for Personal Communication Devices |
US8661340B2 (en) | 2007-09-13 | 2014-02-25 | Apple Inc. | Input methods for device having multi-language environment |
US20090076825A1 (en) | 2007-09-13 | 2009-03-19 | Bionica Corporation | Method of enhancing sound for hearing impaired individuals |
US20090074214A1 (en) | 2007-09-13 | 2009-03-19 | Bionica Corporation | Assistive listening system with plug in enhancement platform and communication port to download user preferred processing algorithms |
JP4990077B2 (en) | 2007-09-14 | 2012-08-01 | 株式会社日立製作所 | Navigation device |
US9734465B2 (en) | 2007-09-14 | 2017-08-15 | Ricoh Co., Ltd | Distributed workflow-enabled system |
KR100920267B1 (en) | 2007-09-17 | 2009-10-05 | 한국전자통신연구원 | System for voice communication analysis and method thereof |
US8706476B2 (en) | 2007-09-18 | 2014-04-22 | Ariadne Genomics, Inc. | Natural language processing method by analyzing primitive sentences, logical clauses, clause types and verbal blocks |
KR100919225B1 (en) | 2007-09-19 | 2009-09-28 | 한국전자통신연구원 | The method and apparatus for post-processing conversation error using multilevel check in voice conversation system |
US8583438B2 (en) | 2007-09-20 | 2013-11-12 | Microsoft Corporation | Unnatural prosody detection in speech synthesis |
ATE509345T1 (en) | 2007-09-21 | 2011-05-15 | Boeing Co | VOICED VEHICLE CONTROLS |
US8042053B2 (en) | 2007-09-24 | 2011-10-18 | Microsoft Corporation | Method for making digital documents browseable |
US8069051B2 (en) | 2007-09-25 | 2011-11-29 | Apple Inc. | Zero-gap playback using predictive mixing |
US20090083035A1 (en) | 2007-09-25 | 2009-03-26 | Ritchie Winson Huang | Text pre-processing for text-to-speech generation |
US20090079622A1 (en) | 2007-09-26 | 2009-03-26 | Broadcom Corporation | Sharing of gps information between mobile devices |
JP5360597B2 (en) | 2007-09-28 | 2013-12-04 | 日本電気株式会社 | Data classification method and data classification device |
US9053089B2 (en) | 2007-10-02 | 2015-06-09 | Apple Inc. | Part-of-speech tagging using latent analogy |
US8923491B2 (en) | 2007-10-03 | 2014-12-30 | At&T Intellectual Property I, L.P. | System and method for connecting to addresses received in spoken communications |
TWI360761B (en) | 2007-10-03 | 2012-03-21 | Inventec Corp | An electronic apparatus and a method for automatic |
US8515095B2 (en) | 2007-10-04 | 2013-08-20 | Apple Inc. | Reducing annoyance by managing the acoustic noise produced by a device |
US7995732B2 (en) | 2007-10-04 | 2011-08-09 | At&T Intellectual Property I, Lp | Managing audio in a multi-source audio environment |
US8165886B1 (en) | 2007-10-04 | 2012-04-24 | Great Northern Research LLC | Speech interface system and method for control and interaction with applications on a computing system |
US8462959B2 (en) | 2007-10-04 | 2013-06-11 | Apple Inc. | Managing acoustic noise produced by a device |
US8036901B2 (en) | 2007-10-05 | 2011-10-11 | Sensory, Incorporated | Systems and methods of performing speech recognition using sensory inputs of human position |
IL186505A0 (en) | 2007-10-08 | 2008-01-20 | Excelang Ltd | Grammar checker |
US8655643B2 (en) | 2007-10-09 | 2014-02-18 | Language Analytics Llc | Method and system for adaptive transliteration |
US8139763B2 (en) | 2007-10-10 | 2012-03-20 | Spansion Llc | Randomized RSA-based cryptographic exponentiation resistant to side channel and fault attacks |
US20090097634A1 (en) | 2007-10-16 | 2009-04-16 | Ullas Balan Nambiar | Method and System for Call Processing |
US8594996B2 (en) | 2007-10-17 | 2013-11-26 | Evri Inc. | NLP-based entity recognition and disambiguation |
JP2009098490A (en) | 2007-10-18 | 2009-05-07 | Kddi Corp | Device for editing speech recognition result, speech recognition device and computer program |
US8209384B2 (en) | 2007-10-23 | 2012-06-26 | Yahoo! Inc. | Persistent group-based instant messaging |
US20090112677A1 (en) | 2007-10-24 | 2009-04-30 | Rhett Randolph L | Method for automatically developing suggested optimal work schedules from unsorted group and individual task lists |
US8606562B2 (en) | 2007-10-25 | 2013-12-10 | Blackberry Limited | Disambiguated text message retype function |
US8000972B2 (en) | 2007-10-26 | 2011-08-16 | Sony Corporation | Remote controller with speech recognition |
US8280885B2 (en) | 2007-10-29 | 2012-10-02 | Cornell University | System and method for automatically summarizing fine-grained opinions in digital text |
US20090112572A1 (en) | 2007-10-30 | 2009-04-30 | Karl Ola Thorn | System and method for input of text to an application operating on a device |
JP2009110300A (en) | 2007-10-30 | 2009-05-21 | Nippon Telegr & Teleph Corp <Ntt> | Information home appliance network control device, information home appliance network control system, information home appliance network control method, and program |
US8566098B2 (en) | 2007-10-30 | 2013-10-22 | At&T Intellectual Property I, L.P. | System and method for improving synthesized speech interactions of a spoken dialog system |
US7840447B2 (en) | 2007-10-30 | 2010-11-23 | Leonard Kleinrock | Pricing and auctioning of bundled items among multiple sellers and buyers |
US9063979B2 (en) | 2007-11-01 | 2015-06-23 | Ebay, Inc. | Analyzing event streams of user sessions |
US8010614B1 (en) | 2007-11-01 | 2011-08-30 | Bitdefender IPR Management Ltd. | Systems and methods for generating signatures for electronic communication classification |
US7983997B2 (en) | 2007-11-02 | 2011-07-19 | Florida Institute For Human And Machine Cognition, Inc. | Interactive complex task teaching system that allows for natural language input, recognizes a user's intent, and automatically performs tasks in document object model (DOM) nodes |
CN101424973A (en) | 2007-11-02 | 2009-05-06 | 夏普株式会社 | Input device |
US8055296B1 (en) | 2007-11-06 | 2011-11-08 | Sprint Communications Company L.P. | Head-up display communication system and method |
US8065152B2 (en) | 2007-11-08 | 2011-11-22 | Demand Media, Inc. | Platform for enabling voice commands to resolve phoneme based domain name registrations |
US20090125813A1 (en) | 2007-11-09 | 2009-05-14 | Zhongnan Shen | Method and system for processing multiple dialog sessions in parallel |
US20090125299A1 (en) | 2007-11-09 | 2009-05-14 | Jui-Chang Wang | Speech recognition system |
JP4926004B2 (en) | 2007-11-12 | 2012-05-09 | 株式会社リコー | Document processing apparatus, document processing method, and document processing program |
DE102008051756A1 (en) | 2007-11-12 | 2009-05-14 | Volkswagen Ag | Multimodal user interface of a driver assistance system for entering and presenting information |
US20090125602A1 (en) | 2007-11-14 | 2009-05-14 | International Business Machines Corporation | Automatic priority adjustment for incoming emails |
US7890525B2 (en) | 2007-11-14 | 2011-02-15 | International Business Machines Corporation | Foreign language abbreviation translation in an instant messaging system |
US8294669B2 (en) | 2007-11-19 | 2012-10-23 | Palo Alto Research Center Incorporated | Link target accuracy in touch-screen mobile devices by layout adjustment |
US8112280B2 (en) | 2007-11-19 | 2012-02-07 | Sensory, Inc. | Systems and methods of performing speech recognition with barge-in for use in a bluetooth system |
US8620662B2 (en) | 2007-11-20 | 2013-12-31 | Apple Inc. | Context-aware unit selection |
US20150046537A1 (en) | 2007-11-21 | 2015-02-12 | Vdoqwest, Inc., A Delaware Corporation | Retrieving video annotation metadata using a p2p network and copyright free indexes |
US20110246471A1 (en) | 2010-04-06 | 2011-10-06 | Selim Shlomo Rakib | Retrieving video annotation metadata using a p2p network |
CN101448340B (en) | 2007-11-26 | 2011-12-07 | 联想(北京)有限公司 | Mobile terminal state detection method and system and mobile terminal |
TWI373708B (en) | 2007-11-27 | 2012-10-01 | Htc Corp | Power management method for handheld electronic device |
US8213999B2 (en) | 2007-11-27 | 2012-07-03 | Htc Corporation | Controlling method and system for handheld communication device and recording medium using the same |
ATE541270T1 (en) | 2007-11-28 | 2012-01-15 | Fujitsu Ltd | METAL TUBE MANAGED BY WIRELESS IC LABEL AND WIRELESS IC LABEL |
US8190596B2 (en) | 2007-11-28 | 2012-05-29 | International Business Machines Corporation | Method for assembly of personalized enterprise information integrators over conjunctive queries |
JP2009134409A (en) | 2007-11-29 | 2009-06-18 | Sony Ericsson Mobilecommunications Japan Inc | Reminder device, reminder method, reminder program, and portable terminal device |
US7805286B2 (en) | 2007-11-30 | 2010-09-28 | Bose Corporation | System and method for sound system simulation |
US8543622B2 (en) | 2007-12-07 | 2013-09-24 | Patrick Giblin | Method and system for meta-tagging media content and distribution |
EP2068537B1 (en) | 2007-12-07 | 2011-07-13 | Research In Motion Limited | System and method for event-dependent state activation for a mobile communication device |
US8385588B2 (en) | 2007-12-11 | 2013-02-26 | Eastman Kodak Company | Recording audio metadata for stored images |
JP5493267B2 (en) | 2007-12-11 | 2014-05-14 | 大日本印刷株式会社 | Product search device and product search method |
US8140335B2 (en) | 2007-12-11 | 2012-03-20 | Voicebox Technologies, Inc. | System and method for providing a natural language voice user interface in an integrated voice navigation services environment |
US8275607B2 (en) | 2007-12-12 | 2012-09-25 | Microsoft Corporation | Semi-supervised part-of-speech tagging |
US9767681B2 (en) | 2007-12-12 | 2017-09-19 | Apple Inc. | Handheld electronic devices with remote control functionality and gesture recognition |
US20090158423A1 (en) | 2007-12-14 | 2009-06-18 | Symbol Technologies, Inc. | Locking mobile device cradle |
US20090158350A1 (en) * | 2007-12-14 | 2009-06-18 | United Video Properties, Inc. | Systems and methods for providing enhanced recording options of media content |
US20090158173A1 (en) | 2007-12-17 | 2009-06-18 | Palahnuk Samuel Louis | Communications system with dynamic calendar |
US8145196B2 (en) | 2007-12-18 | 2012-03-27 | Apple Inc. | Creation and management of voicemail greetings for mobile communication devices |
JP5327054B2 (en) | 2007-12-18 | 2013-10-30 | 日本電気株式会社 | Pronunciation variation rule extraction device, pronunciation variation rule extraction method, and pronunciation variation rule extraction program |
KR101300839B1 (en) | 2007-12-18 | 2013-09-10 | 삼성전자주식회사 | Voice query extension method and system |
US8095680B2 (en) | 2007-12-20 | 2012-01-10 | Telefonaktiebolaget Lm Ericsson (Publ) | Real-time network transport protocol interface method and apparatus |
US10002189B2 (en) | 2007-12-20 | 2018-06-19 | Apple Inc. | Method and apparatus for searching using an active ontology |
US8063879B2 (en) | 2007-12-20 | 2011-11-22 | Research In Motion Limited | Method and handheld electronic device including first input component and second touch sensitive input component |
US20090164937A1 (en) | 2007-12-20 | 2009-06-25 | Alden Alviar | Scroll Apparatus and Method for Manipulating Data on an Electronic Device Display |
CA2710245C (en) | 2007-12-21 | 2018-01-23 | Bce Inc. | Method and apparatus for interrupting an active telephony session to deliver information to a subscriber |
JP5239328B2 (en) | 2007-12-21 | 2013-07-17 | ソニー株式会社 | Information processing apparatus and touch motion recognition method |
US20090164301A1 (en) | 2007-12-21 | 2009-06-25 | Yahoo! Inc. | Targeted Ad System Using Metadata |
US8019604B2 (en) | 2007-12-21 | 2011-09-13 | Motorola Mobility, Inc. | Method and apparatus for uniterm discovery and voice-to-voice search on mobile device |
KR20090071077A (en) | 2007-12-27 | 2009-07-01 | 엘지전자 주식회사 | Navigation apparatus and method for providing information of tbt(turn-by-turn position) |
US8583416B2 (en) | 2007-12-27 | 2013-11-12 | Fluential, Llc | Robust information extraction from utterances |
US8219407B1 (en) | 2007-12-27 | 2012-07-10 | Great Northern Research, LLC | Method for processing the output of a speech recognizer |
US20090172108A1 (en) | 2007-12-28 | 2009-07-02 | Surgo | Systems and methods for a telephone-accessible message communication system |
US8373549B2 (en) | 2007-12-31 | 2013-02-12 | Apple Inc. | Tactile feedback in an electronic device |
US9330720B2 (en) | 2008-01-03 | 2016-05-03 | Apple Inc. | Methods and apparatus for altering audio output signals |
US8405621B2 (en) | 2008-01-06 | 2013-03-26 | Apple Inc. | Variable rate media playback methods for electronic devices with touch interfaces |
US20090177966A1 (en) | 2008-01-06 | 2009-07-09 | Apple Inc. | Content Sheet for Media Player |
US7609179B2 (en) | 2008-01-08 | 2009-10-27 | International Business Machines Corporation | Method for compressed data with reduced dictionary sizes by coding value prefixes |
US20090204402A1 (en) | 2008-01-09 | 2009-08-13 | 8 Figure, Llc | Method and apparatus for creating customized podcasts with multiple text-to-speech voices |
US8478578B2 (en) | 2008-01-09 | 2013-07-02 | Fluential, Llc | Mobile speech-to-speech interpretation system |
US8232973B2 (en) | 2008-01-09 | 2012-07-31 | Apple Inc. | Method, device, and graphical user interface providing word recommendations for text input |
WO2009087860A1 (en) | 2008-01-10 | 2009-07-16 | Brother Kogyo Kabushiki Kaisha | Voice interactive device and computer-readable medium containing voice interactive program |
JP5266761B2 (en) | 2008-01-10 | 2013-08-21 | 日産自動車株式会社 | Information guidance system and its recognition dictionary database update method |
US7870133B2 (en) | 2008-01-14 | 2011-01-11 | Infosys Technologies Ltd. | Method for semantic based storage and retrieval of information |
US10176827B2 (en) | 2008-01-15 | 2019-01-08 | Verint Americas Inc. | Active lab |
EP2081185B1 (en) | 2008-01-16 | 2014-11-26 | Nuance Communications, Inc. | Speech recognition on large lists using fragments |
US20090187950A1 (en) | 2008-01-18 | 2009-07-23 | At&T Knowledge Ventures, L.P. | Audible menu system |
US20090187577A1 (en) | 2008-01-20 | 2009-07-23 | Aviv Reznik | System and Method Providing Audio-on-Demand to a User's Personal Online Device as Part of an Online Audio Community |
ITPO20080002A1 (en) | 2008-01-22 | 2009-07-23 | Riccardo Vieri | SYSTEM AND METHOD FOR THE CONTEXTUAL ADVERTISING GENERATION DURING THE SENDING OF SMS, ITS DEVICE AND INTERFACE. |
JP2009177440A (en) | 2008-01-24 | 2009-08-06 | Nec Corp | Mobile phone unit and control method thereof |
US8175882B2 (en) | 2008-01-25 | 2012-05-08 | International Business Machines Corporation | Method and system for accent correction |
US20120284015A1 (en) | 2008-01-28 | 2012-11-08 | William Drewes | Method for Increasing the Accuracy of Subject-Specific Statistical Machine Translation (SMT) |
US20090192782A1 (en) | 2008-01-28 | 2009-07-30 | William Drewes | Method for increasing the accuracy of statistical machine translation (SMT) |
US8223988B2 (en) | 2008-01-29 | 2012-07-17 | Qualcomm Incorporated | Enhanced blind source separation algorithm for highly correlated mixtures |
CN101500041A (en) | 2008-01-30 | 2009-08-05 | 中兴通讯股份有限公司 | Call control method and apparatus |
CN101981987B (en) | 2008-01-30 | 2014-12-03 | 谷歌公司 | Notification of mobile device events |
CN101499156A (en) | 2008-01-31 | 2009-08-05 | 上海亿动信息技术有限公司 | Advertisement issuance control method and apparatus based on multi-advertisement information issuing apparatus |
US7840581B2 (en) | 2008-02-01 | 2010-11-23 | Realnetworks, Inc. | Method and system for improving the quality of deep metadata associated with media content |
KR20090085376A (en) | 2008-02-04 | 2009-08-07 | 삼성전자주식회사 | Service method and apparatus for using speech synthesis of text message |
US10269024B2 (en) | 2008-02-08 | 2019-04-23 | Outbrain Inc. | Systems and methods for identifying and measuring trends in consumer content demand within vertically associated websites and related content |
US8000956B2 (en) | 2008-02-08 | 2011-08-16 | Xerox Corporation | Semantic compatibility checking for automatic correction and discovery of named entities |
KR101334066B1 (en) | 2008-02-11 | 2013-11-29 | 이점식 | Self-evolving Artificial Intelligent cyber robot system and offer method |
US8195656B2 (en) | 2008-02-13 | 2012-06-05 | Yahoo, Inc. | Social network search |
US8099289B2 (en) | 2008-02-13 | 2012-01-17 | Sensory, Inc. | Voice interface and search for electronic devices including bluetooth headsets and remote systems |
US20090210391A1 (en) | 2008-02-14 | 2009-08-20 | Hall Stephen G | Method and system for automated search for, and retrieval and distribution of, information |
JP2009193448A (en) | 2008-02-15 | 2009-08-27 | Oki Electric Ind Co Ltd | Dialog system, method, and program |
JP2009193532A (en) | 2008-02-18 | 2009-08-27 | Oki Electric Ind Co Ltd | Dialogue management device, method, and program, and consciousness extraction system |
US8165884B2 (en) | 2008-02-15 | 2012-04-24 | Microsoft Corporation | Layered prompting: self-calibrating instructional prompting for verbal interfaces |
JP2009193457A (en) | 2008-02-15 | 2009-08-27 | Oki Electric Ind Co Ltd | Information retrieval device, method and program |
EP2094032A1 (en) | 2008-02-19 | 2009-08-26 | Deutsche Thomson OHG | Audio signal, method and apparatus for encoding or transmitting the same and method and apparatus for processing the same |
EP2243303A1 (en) | 2008-02-20 | 2010-10-27 | Koninklijke Philips Electronics N.V. | Audio device and method of operation therefor |
US20090215466A1 (en) | 2008-02-22 | 2009-08-27 | Darcy Ahl | Mobile phone based system for disabling a cell phone while traveling |
US8065143B2 (en) | 2008-02-22 | 2011-11-22 | Apple Inc. | Providing text input using speech data and non-speech data |
US8706474B2 (en) | 2008-02-23 | 2014-04-22 | Fair Isaac Corporation | Translation of entity names based on source document publication date, and frequency and co-occurrence of the entity names |
US8015144B2 (en) | 2008-02-26 | 2011-09-06 | Microsoft Corporation | Learning transportation modes from raw GPS data |
JP4433061B2 (en) | 2008-02-27 | 2010-03-17 | 株式会社デンソー | Driving support system |
US8068604B2 (en) | 2008-12-19 | 2011-11-29 | Computer Product Introductions Corporation | Method and system for event notifications |
US9049255B2 (en) | 2008-02-29 | 2015-06-02 | Blackberry Limited | Visual event notification on a handheld communications device |
EP2096840B1 (en) | 2008-02-29 | 2012-07-04 | Research In Motion Limited | Visual event notification on a handheld communications device |
US20090221274A1 (en) | 2008-02-29 | 2009-09-03 | Venkatakrishnan Poornima | System, method and device for enabling alternative call handling routines for incoming calls |
JP2009205579A (en) | 2008-02-29 | 2009-09-10 | Toshiba Corp | Speech translation device and program |
US20090228897A1 (en) * | 2008-03-04 | 2009-09-10 | Murray Frank H | Bidirectional Control of Media Players |
US8201109B2 (en) | 2008-03-04 | 2012-06-12 | Apple Inc. | Methods and graphical user interfaces for editing on a portable multifunction device |
US8650507B2 (en) | 2008-03-04 | 2014-02-11 | Apple Inc. | Selecting of text using gestures |
US8205157B2 (en) | 2008-03-04 | 2012-06-19 | Apple Inc. | Methods and graphical user interfaces for conducting searches on a portable multifunction device |
US20090228273A1 (en) | 2008-03-05 | 2009-09-10 | Microsoft Corporation | Handwriting-based user interface for correction of speech recognition errors |
US8255224B2 (en) | 2008-03-07 | 2012-08-28 | Google Inc. | Voice recognition grammar selection based on context |
US20090228439A1 (en) | 2008-03-07 | 2009-09-10 | Microsoft Corporation | Intent-aware search |
US8587402B2 (en) | 2008-03-07 | 2013-11-19 | Palm, Inc. | Context aware data processing in mobile computing device |
US8380512B2 (en) | 2008-03-10 | 2013-02-19 | Yahoo! Inc. | Navigation using a search engine and phonetic voice recognition |
US8364486B2 (en) | 2008-03-12 | 2013-01-29 | Intelligent Mechatronic Systems Inc. | Speech understanding method and system |
US20090235280A1 (en) | 2008-03-12 | 2009-09-17 | Xerox Corporation | Event extraction system for electronic messages |
US20090234655A1 (en) | 2008-03-13 | 2009-09-17 | Jason Kwon | Mobile electronic device with active speech recognition |
US20090235176A1 (en) | 2008-03-14 | 2009-09-17 | Madhavi Jayanthi | Social interaction system for facilitating display of current location of friends and location of businesses of interest |
US20090234638A1 (en) | 2008-03-14 | 2009-09-17 | Microsoft Corporation | Use of a Speech Grammar to Recognize Instant Message Input |
US7958136B1 (en) | 2008-03-18 | 2011-06-07 | Google Inc. | Systems and methods for identifying similar documents |
JP2009223840A (en) | 2008-03-19 | 2009-10-01 | Fujitsu Ltd | Schedule management program, schedule management device and schedule management method |
US20090239552A1 (en) | 2008-03-24 | 2009-09-24 | Yahoo! Inc. | Location-based opportunistic recommendations |
CN101547396B (en) | 2008-03-24 | 2012-07-04 | 展讯通信(上海)有限公司 | Method for quickly reporting position in emergency calling process |
WO2009117820A1 (en) | 2008-03-25 | 2009-10-01 | E-Lane Systems Inc. | Multi-participant, mixed-initiative voice interaction system |
US20110035434A1 (en) | 2008-03-27 | 2011-02-10 | Markport Limited | Processing of messaging service attributes in communication systems |
US8615388B2 (en) | 2008-03-28 | 2013-12-24 | Microsoft Corporation | Intra-language statistical machine translation |
US20090248456A1 (en) | 2008-03-28 | 2009-10-01 | Passkey International, Inc. | Notifications and reports in a reservation system |
EP2107553B1 (en) | 2008-03-31 | 2011-05-18 | Harman Becker Automotive Systems GmbH | Method for determining barge-in |
US7472061B1 (en) | 2008-03-31 | 2008-12-30 | International Business Machines Corporation | Systems and methods for building a native language phoneme lexicon having native pronunciations of non-native words derived from non-native pronunciations |
US20090249198A1 (en) | 2008-04-01 | 2009-10-01 | Yahoo! Inc. | Techniques for input recogniton and completion |
US8417298B2 (en) | 2008-04-01 | 2013-04-09 | Apple Inc. | Mounting structures for portable electronic devices |
US8312376B2 (en) | 2008-04-03 | 2012-11-13 | Microsoft Corporation | Bookmark interpretation service |
TWI446780B (en) | 2008-04-03 | 2014-07-21 | Hon Hai Prec Ind Co Ltd | Communication apparatus and method |
US20090253457A1 (en) | 2008-04-04 | 2009-10-08 | Apple Inc. | Audio signal processing for certification enhancement in a handheld wireless communications device |
US8996376B2 (en) | 2008-04-05 | 2015-03-31 | Apple Inc. | Intelligent text-to-speech conversion |
KR101491581B1 (en) | 2008-04-07 | 2015-02-24 | 삼성전자주식회사 | Correction System for spelling error and method thereof |
JPWO2009125710A1 (en) | 2008-04-08 | 2011-08-04 | 株式会社エヌ・ティ・ティ・ドコモ | Media processing server apparatus and media processing method |
US8958848B2 (en) | 2008-04-08 | 2015-02-17 | Lg Electronics Inc. | Mobile terminal and menu control method thereof |
KR20090107365A (en) | 2008-04-08 | 2009-10-13 | 엘지전자 주식회사 | Mobile terminal and its menu control method |
KR20090107364A (en) | 2008-04-08 | 2009-10-13 | 엘지전자 주식회사 | Mobile terminal and its menu control method |
US8285737B1 (en) | 2008-04-10 | 2012-10-09 | Google Inc. | Selecting content for publication |
JP4656177B2 (en) | 2008-04-14 | 2011-03-23 | トヨタ自動車株式会社 | Navigation device, operation unit display method |
US7889101B2 (en) | 2008-04-14 | 2011-02-15 | Alpine Electronics, Inc | Method and apparatus for generating location based reminder message for navigation system |
US8370148B2 (en) | 2008-04-14 | 2013-02-05 | At&T Intellectual Property I, L.P. | System and method for answering a communication notification |
WO2009129315A1 (en) | 2008-04-15 | 2009-10-22 | Mobile Technologies, Llc | System and methods for maintaining speech-to-speech translation in the field |
US8046222B2 (en) | 2008-04-16 | 2011-10-25 | Google Inc. | Segmenting words using scaled probabilities |
US8490050B2 (en) | 2008-04-17 | 2013-07-16 | Microsoft Corporation | Automatic generation of user interfaces |
US8433778B1 (en) | 2008-04-22 | 2013-04-30 | Marvell International Ltd | Device configuration |
US8666824B2 (en) | 2008-04-23 | 2014-03-04 | Dell Products L.P. | Digital media content location and purchasing system |
US8407049B2 (en) | 2008-04-23 | 2013-03-26 | Cogi, Inc. | Systems and methods for conversation enhancement |
US8972432B2 (en) | 2008-04-23 | 2015-03-03 | Google Inc. | Machine translation using information retrieval |
US8249857B2 (en) | 2008-04-24 | 2012-08-21 | International Business Machines Corporation | Multilingual administration of enterprise data with user selected target language translation |
US8594995B2 (en) | 2008-04-24 | 2013-11-26 | Nuance Communications, Inc. | Multilingual asynchronous communications of speech messages recorded in digital media files |
US8121837B2 (en) | 2008-04-24 | 2012-02-21 | Nuance Communications, Inc. | Adjusting a speech engine for a mobile computing device based on background noise |
US8082148B2 (en) | 2008-04-24 | 2011-12-20 | Nuance Communications, Inc. | Testing a grammar used in speech recognition for reliability in a plurality of operating environments having different background noise |
US8249858B2 (en) | 2008-04-24 | 2012-08-21 | International Business Machines Corporation | Multilingual administration of enterprise data with default target languages |
US8194827B2 (en) | 2008-04-29 | 2012-06-05 | International Business Machines Corporation | Secure voice transaction method and system |
US8521512B2 (en) | 2008-04-30 | 2013-08-27 | Deep Sky Concepts, Inc | Systems and methods for natural language communication with a computer |
US8693698B2 (en) | 2008-04-30 | 2014-04-08 | Qualcomm Incorporated | Method and apparatus to reduce non-linear distortion in mobile computing devices |
US20090274376A1 (en) | 2008-05-05 | 2009-11-05 | Yahoo! Inc. | Method for efficiently building compact models for large multi-class text classification |
US8254829B1 (en) | 2008-05-09 | 2012-08-28 | Sprint Communications Company L.P. | Network media service with track delivery adapted to a user cadence |
US8400405B2 (en) | 2008-05-09 | 2013-03-19 | Research In Motion Limited | Handheld electronic device and associated method enabling text input in a language employing non-roman characters |
US8219115B1 (en) | 2008-05-12 | 2012-07-10 | Google Inc. | Location based reminders |
US20130275899A1 (en) | 2010-01-18 | 2013-10-17 | Apple Inc. | Application Gateway for Providing Different User Interfaces for Limited Distraction and Non-Limited Distraction Contexts |
US10496753B2 (en) | 2010-01-18 | 2019-12-03 | Apple Inc. | Automatically adapting user interfaces for hands-free interaction |
US8516562B2 (en) | 2008-05-13 | 2013-08-20 | Veritrix, Inc. | Multi-channel multi-factor authentication |
US9965035B2 (en) | 2008-05-13 | 2018-05-08 | Apple Inc. | Device, method, and graphical user interface for synchronizing two or more displays |
US8174503B2 (en) | 2008-05-17 | 2012-05-08 | David H. Cain | Touch-based authentication of a mobile device through user generated pattern creation |
US8131267B2 (en) | 2008-05-19 | 2012-03-06 | Tbm, Llc | Interactive voice access and retrieval of information |
DE102008024258A1 (en) | 2008-05-20 | 2009-11-26 | Siemens Aktiengesellschaft | A method for classifying and removing unwanted portions from a speech recognition utterance |
US10203861B2 (en) | 2008-05-21 | 2019-02-12 | Please Don't Go, LLC. | Messaging window overlay for a browser |
US8285344B2 (en) | 2008-05-21 | 2012-10-09 | DP Technlogies, Inc. | Method and apparatus for adjusting audio for a user environment |
US20090292987A1 (en) | 2008-05-22 | 2009-11-26 | International Business Machines Corporation | Formatting selected content of an electronic document based on analyzed formatting |
US8082498B2 (en) | 2008-05-27 | 2011-12-20 | Appfolio, Inc. | Systems and methods for automatic spell checking of dynamically generated web pages |
US9305548B2 (en) | 2008-05-27 | 2016-04-05 | Voicebox Technologies Corporation | System and method for an integrated, multi-modal, multi-device natural language voice services environment |
US8589161B2 (en) | 2008-05-27 | 2013-11-19 | Voicebox Technologies, Inc. | System and method for an integrated, multi-modal, multi-device natural language voice services environment |
US20130100268A1 (en) | 2008-05-27 | 2013-04-25 | University Health Network | Emergency detection and response system and method |
KR101462932B1 (en) | 2008-05-28 | 2014-12-04 | 엘지전자 주식회사 | Mobile terminal and text correction method |
US20090326938A1 (en) | 2008-05-28 | 2009-12-31 | Nokia Corporation | Multiword text correction |
US8473279B2 (en) | 2008-05-30 | 2013-06-25 | Eiman Al-Shammari | Lemmatizing, stemming, and query expansion method and system |
US8126435B2 (en) | 2008-05-30 | 2012-02-28 | Hewlett-Packard Development Company, L.P. | Techniques to manage vehicle communications |
US8694355B2 (en) | 2008-05-30 | 2014-04-08 | Sri International | Method and apparatus for automated assistance with task management |
US8233366B2 (en) | 2008-06-02 | 2012-07-31 | Apple Inc. | Context-based error indication methods and apparatus |
US20090298529A1 (en) | 2008-06-03 | 2009-12-03 | Symbol Technologies, Inc. | Audio HTML (aHTML): Audio Access to Web/Data |
KR101631496B1 (en) | 2008-06-03 | 2016-06-17 | 삼성전자주식회사 | Robot apparatus and method for registrating contracted commander thereof |
JP5136228B2 (en) | 2008-06-05 | 2013-02-06 | 日本電気株式会社 | Work environment automatic save and restore system, work environment auto save and restore method, and work environment auto save and restore program |
JP5377889B2 (en) | 2008-06-05 | 2013-12-25 | 日本放送協会 | Language processing apparatus and program |
US8140326B2 (en) | 2008-06-06 | 2012-03-20 | Fuji Xerox Co., Ltd. | Systems and methods for reducing speech intelligibility while preserving environmental sounds |
US8831948B2 (en) | 2008-06-06 | 2014-09-09 | At&T Intellectual Property I, L.P. | System and method for synthetically generated speech describing media content |
US8180630B2 (en) | 2008-06-06 | 2012-05-15 | Zi Corporation Of Canada, Inc. | Systems and methods for an automated personalized dictionary generator for portable devices |
TWM348993U (en) | 2008-06-06 | 2009-01-11 | Ming-Ying Chen | Smart voice-controlled device to control home appliance with infrared controller |
US8464150B2 (en) | 2008-06-07 | 2013-06-11 | Apple Inc. | Automatic language identification for dynamic text processing |
US9626363B2 (en) | 2008-06-08 | 2017-04-18 | Apple Inc. | System and method for placeshifting media playback |
KR100988397B1 (en) | 2008-06-09 | 2010-10-19 | 엘지전자 주식회사 | Mobile terminal and text correcting method in the same |
US20090306967A1 (en) | 2008-06-09 | 2009-12-10 | J.D. Power And Associates | Automatic Sentiment Analysis of Surveys |
US8219397B2 (en) | 2008-06-10 | 2012-07-10 | Nuance Communications, Inc. | Data processing system for autonomously building speech identification and tagging data |
DE602008005428D1 (en) | 2008-06-11 | 2011-04-21 | Exb Asset Man Gmbh | Apparatus and method with improved text input mechanism |
US20090313564A1 (en) | 2008-06-12 | 2009-12-17 | Apple Inc. | Systems and methods for adjusting playback of media files based on previous usage |
US8527876B2 (en) | 2008-06-12 | 2013-09-03 | Apple Inc. | System and methods for adjusting graphical representations of media files based on previous usage |
US20090313020A1 (en) | 2008-06-12 | 2009-12-17 | Nokia Corporation | Text-to-speech user interface control |
KR101513615B1 (en) | 2008-06-12 | 2015-04-20 | 엘지전자 주식회사 | Mobile terminal and voice recognition method |
US8140330B2 (en) | 2008-06-13 | 2012-03-20 | Robert Bosch Gmbh | System and method for detecting repeated patterns in dialog systems |
US20090313023A1 (en) | 2008-06-17 | 2009-12-17 | Ralph Jones | Multilingual text-to-speech system |
DE102008028885A1 (en) | 2008-06-18 | 2009-12-31 | Epcos Ag | Method for tuning a resonance frequency of a piezoelectric component |
US9510044B1 (en) | 2008-06-18 | 2016-11-29 | Gracenote, Inc. | TV content segmentation, categorization and identification and time-aligned applications |
AU2009260033A1 (en) | 2008-06-19 | 2009-12-23 | Wize Technologies, Inc. | System and method for aggregating and summarizing product/topic sentiment |
CA2727951A1 (en) | 2008-06-19 | 2009-12-23 | E-Lane Systems Inc. | Communication system with voice mail access and call by spelling functionality |
GB2462800A (en) | 2008-06-20 | 2010-02-24 | New Voice Media Ltd | Monitoring a conversation between an agent and a customer and performing real time analytics on the audio signal for determining future handling of the call |
WO2009156438A1 (en) | 2008-06-24 | 2009-12-30 | Llinxx | Method and system for entering an expression |
US9081590B2 (en) | 2008-06-24 | 2015-07-14 | Microsoft Technology Licensing, Llc | Multimodal input using scratchpad graphical user interface to edit speech text input with keyboard input |
US8300801B2 (en) | 2008-06-26 | 2012-10-30 | Centurylink Intellectual Property Llc | System and method for telephone based noise cancellation |
WO2009156978A1 (en) | 2008-06-26 | 2009-12-30 | Intuitive User Interfaces Ltd | System and method for intuitive user interaction |
US8423288B2 (en) | 2009-11-30 | 2013-04-16 | Apple Inc. | Dynamic alerts for calendar events |
US8364481B2 (en) | 2008-07-02 | 2013-01-29 | Google Inc. | Speech recognition with parallel recognition tasks |
US20100005085A1 (en) | 2008-07-03 | 2010-01-07 | Oracle International Corporation | Creating relationship maps from enterprise application system data |
US20110112837A1 (en) | 2008-07-03 | 2011-05-12 | Mobiter Dicta Oy | Method and device for converting speech |
KR101059631B1 (en) | 2008-07-04 | 2011-08-25 | 야후! 인크. | Translator with Automatic Input / Output Interface and Its Interfacing Method |
US8478592B2 (en) | 2008-07-08 | 2013-07-02 | Nuance Communications, Inc. | Enhancing media playback with speech recognition |
JP4710931B2 (en) | 2008-07-09 | 2011-06-29 | ソニー株式会社 | Learning device, learning method, and program |
US8781833B2 (en) | 2008-07-17 | 2014-07-15 | Nuance Communications, Inc. | Speech recognition semantic classification training |
US8521761B2 (en) | 2008-07-18 | 2013-08-27 | Google Inc. | Transliteration for query expansion |
US8166019B1 (en) | 2008-07-21 | 2012-04-24 | Sprint Communications Company L.P. | Providing suggested actions in response to textual communications |
KR20100010860A (en) | 2008-07-23 | 2010-02-02 | 엘지전자 주식회사 | Mobile terminal and event control method thereof |
JP5791861B2 (en) | 2008-07-25 | 2015-10-07 | シャープ株式会社 | Information processing apparatus and information processing method |
JPWO2010013369A1 (en) | 2008-07-30 | 2012-01-05 | 三菱電機株式会社 | Voice recognition device |
US8386485B2 (en) | 2008-07-31 | 2013-02-26 | George Mason Intellectual Properties, Inc. | Case-based framework for collaborative semantic search |
US20100030549A1 (en) | 2008-07-31 | 2010-02-04 | Lee Michael M | Mobile device having human language translation capability with positional feedback |
US8041848B2 (en) | 2008-08-04 | 2011-10-18 | Apple Inc. | Media processing method and device |
US8589149B2 (en) | 2008-08-05 | 2013-11-19 | Nuance Communications, Inc. | Probability-based approach to recognition of user-entered data |
US9317589B2 (en) | 2008-08-07 | 2016-04-19 | International Business Machines Corporation | Semantic search by means of word sense disambiguation using a lexicon |
US20110131038A1 (en) | 2008-08-11 | 2011-06-02 | Satoshi Oyaizu | Exception dictionary creating unit, exception dictionary creating method, and program therefor, as well as speech recognition unit and speech recognition method |
KR100998566B1 (en) | 2008-08-11 | 2010-12-07 | 엘지전자 주식회사 | Method And Apparatus Of Translating Language Using Voice Recognition |
JP4577428B2 (en) | 2008-08-11 | 2010-11-10 | ソニー株式会社 | Display device, display method, and program |
US8170969B2 (en) | 2008-08-13 | 2012-05-01 | Siemens Aktiengesellschaft | Automated computation of semantic similarity of pairs of named entity phrases using electronic document corpora as background knowledge |
US8520979B2 (en) | 2008-08-19 | 2013-08-27 | Digimarc Corporation | Methods and systems for content processing |
US8805110B2 (en) | 2008-08-19 | 2014-08-12 | Digimarc Corporation | Methods and systems for content processing |
JP5459214B2 (en) | 2008-08-20 | 2014-04-02 | 日本電気株式会社 | Language model creation device, language model creation method, speech recognition device, speech recognition method, program, and recording medium |
US20100050064A1 (en) | 2008-08-22 | 2010-02-25 | At & T Labs, Inc. | System and method for selecting a multimedia presentation to accompany text |
US8112269B2 (en) | 2008-08-25 | 2012-02-07 | Microsoft Corporation | Determining utility of a question |
US8117136B2 (en) | 2008-08-29 | 2012-02-14 | Hewlett-Packard Development Company, L.P. | Relationship management on a mobile computing device |
WO2010022561A1 (en) | 2008-08-29 | 2010-03-04 | Mediatek (Hefei) Inc. | Method for playing voice guidance and navigation device using the same |
US20100057435A1 (en) | 2008-08-29 | 2010-03-04 | Kent Justin R | System and method for speech-to-speech translation |
US8442248B2 (en) | 2008-09-03 | 2013-05-14 | Starkey Laboratories, Inc. | Systems and methods for managing wireless communication links for hearing assistance devices |
US8380959B2 (en) | 2008-09-05 | 2013-02-19 | Apple Inc. | Memory management system and method |
US20100063825A1 (en) | 2008-09-05 | 2010-03-11 | Apple Inc. | Systems and Methods for Memory Management and Crossfading in an Electronic Device |
US8768702B2 (en) | 2008-09-05 | 2014-07-01 | Apple Inc. | Multi-tiered voice feedback in an electronic device |
US20100063961A1 (en) | 2008-09-05 | 2010-03-11 | Fotonauts, Inc. | Reverse Tagging of Images in System for Managing and Sharing Digital Images |
US8098262B2 (en) | 2008-09-05 | 2012-01-17 | Apple Inc. | Arbitrary fractional pixel movement |
US7936736B2 (en) | 2008-09-08 | 2011-05-03 | Proctor Jr James Arthur | Enforcing policies in wireless communication using exchanged identities |
US8290971B2 (en) | 2008-09-09 | 2012-10-16 | Applied Systems, Inc. | Method and apparatus for remotely displaying a list by determining a quantity of data to send based on the list size and the display control size |
US8898568B2 (en) | 2008-09-09 | 2014-11-25 | Apple Inc. | Audio user interface |
JP2010066519A (en) | 2008-09-11 | 2010-03-25 | Brother Ind Ltd | Voice interactive device, voice interactive method, and voice interactive program |
US8259082B2 (en) | 2008-09-12 | 2012-09-04 | At&T Intellectual Property I, L.P. | Multimodal portable communication interface for accessing video content |
US8929877B2 (en) | 2008-09-12 | 2015-01-06 | Digimarc Corporation | Methods and systems for content processing |
CN101673274A (en) | 2008-09-12 | 2010-03-17 | 深圳富泰宏精密工业有限公司 | Film subtitle retrieval system and method |
US8756519B2 (en) | 2008-09-12 | 2014-06-17 | Google Inc. | Techniques for sharing content on a web page |
US8239201B2 (en) | 2008-09-13 | 2012-08-07 | At&T Intellectual Property I, L.P. | System and method for audibly presenting selected text |
US20100071003A1 (en) | 2008-09-14 | 2010-03-18 | Modu Ltd. | Content personalization |
US8335778B2 (en) | 2008-09-17 | 2012-12-18 | Oracle International Corporation | System and method for semantic search in an enterprise application |
JP5213605B2 (en) | 2008-09-17 | 2013-06-19 | シャープ株式会社 | COMMUNICATION DEVICE, INFORMATION PRESENTATION DEVICE, COMMUNICATION METHOD, PROGRAM, AND RECORDING MEDIUM |
US8775154B2 (en) | 2008-09-18 | 2014-07-08 | Xerox Corporation | Query translation through dictionary adaptation |
US8326622B2 (en) | 2008-09-23 | 2012-12-04 | International Business Machines Corporation | Dialog filtering for filling out a form |
US20100077350A1 (en) | 2008-09-25 | 2010-03-25 | Microsoft Corporation | Combining elements in presentation of content |
JP2010078979A (en) | 2008-09-26 | 2010-04-08 | Nec Infrontia Corp | Voice recording device, recorded voice retrieval method, and program |
US8560371B2 (en) | 2008-09-26 | 2013-10-15 | Microsoft Corporation | Suggesting things to do during time slots in a schedule |
US20100082328A1 (en) | 2008-09-29 | 2010-04-01 | Apple Inc. | Systems and methods for speech preprocessing in text to speech synthesis |
WO2010037146A2 (en) | 2008-09-29 | 2010-04-01 | Fisher-Rosemount Systems, Inc. | Efficient design and configuration of elements in a process control system |
US8583418B2 (en) | 2008-09-29 | 2013-11-12 | Apple Inc. | Systems and methods of detecting language and natural language strings for text to speech synthesis |
US20100082327A1 (en) | 2008-09-29 | 2010-04-01 | Apple Inc. | Systems and methods for mapping phonemes for text to speech synthesis |
US8352272B2 (en) | 2008-09-29 | 2013-01-08 | Apple Inc. | Systems and methods for text to speech synthesis |
US8396714B2 (en) | 2008-09-29 | 2013-03-12 | Apple Inc. | Systems and methods for concatenation of words in text to speech synthesis |
US20100082653A1 (en) * | 2008-09-29 | 2010-04-01 | Rahul Nair | Event media search |
US8180641B2 (en) | 2008-09-29 | 2012-05-15 | Microsoft Corporation | Sequential speech recognition with two unequal ASR systems |
US8352268B2 (en) | 2008-09-29 | 2013-01-08 | Apple Inc. | Systems and methods for selective rate of speech and speech preferences for text to speech synthesis |
US8712776B2 (en) | 2008-09-29 | 2014-04-29 | Apple Inc. | Systems and methods for selective text to speech synthesis |
US8355919B2 (en) | 2008-09-29 | 2013-01-15 | Apple Inc. | Systems and methods for text normalization for text to speech synthesis |
US8411953B2 (en) | 2008-09-30 | 2013-04-02 | International Business Machines Corporation | Tagging images by determining a set of similar pre-tagged images and extracting prominent tags from that set |
JP2010086230A (en) | 2008-09-30 | 2010-04-15 | Sony Corp | Information processing apparatus, information processing method and program |
US9077526B2 (en) | 2008-09-30 | 2015-07-07 | Apple Inc. | Method and system for ensuring sequential playback of digital media |
US8401178B2 (en) | 2008-09-30 | 2013-03-19 | Apple Inc. | Multiple microphone switching and configuration |
US8798956B2 (en) | 2008-09-30 | 2014-08-05 | Apple Inc. | Method and apparatus for surface sensing input device |
US20100079508A1 (en) | 2008-09-30 | 2010-04-01 | Andrew Hodge | Electronic devices with gaze detection capabilities |
US20100255858A1 (en) | 2008-10-02 | 2010-10-07 | Juhasz Paul R | Dead Zone for Wireless Communication Device |
US8285545B2 (en) | 2008-10-03 | 2012-10-09 | Volkswagen Ag | Voice command acquisition system and method |
US9200913B2 (en) | 2008-10-07 | 2015-12-01 | Telecommunication Systems, Inc. | User interface for predictive traffic |
US9442648B2 (en) | 2008-10-07 | 2016-09-13 | Blackberry Limited | Portable electronic device and method of controlling same |
US8380497B2 (en) | 2008-10-15 | 2013-02-19 | Qualcomm Incorporated | Methods and apparatus for noise estimation |
US8543913B2 (en) | 2008-10-16 | 2013-09-24 | International Business Machines Corporation | Identifying and using textual widgets |
US8170961B2 (en) | 2008-10-16 | 2012-05-01 | At&T Intellectual Property I, L.P. | Text edit tracker that categorizes communications, determines distances between templates, codes templates in color, and uses a morphing score based on edits |
US8539342B1 (en) | 2008-10-16 | 2013-09-17 | Adobe Systems Incorporated | Read-order inference via content sorting |
US20100131899A1 (en) | 2008-10-17 | 2010-05-27 | Darwin Ecosystem Llc | Scannable Cloud |
US20100114887A1 (en) | 2008-10-17 | 2010-05-06 | Google Inc. | Textual Disambiguation Using Social Connections |
US8364487B2 (en) | 2008-10-21 | 2013-01-29 | Microsoft Corporation | Speech recognition system with display information |
US8670546B2 (en) | 2008-10-22 | 2014-03-11 | At&T Intellectual Property I, L.P. | Systems and methods for providing a personalized communication processing service |
US8218397B2 (en) | 2008-10-24 | 2012-07-10 | Qualcomm Incorporated | Audio source proximity estimation using sensor array for noise reduction |
US8577685B2 (en) | 2008-10-24 | 2013-11-05 | At&T Intellectual Property I, L.P. | System and method for targeted advertising |
US8724829B2 (en) | 2008-10-24 | 2014-05-13 | Qualcomm Incorporated | Systems, methods, apparatus, and computer-readable media for coherence detection |
US8190437B2 (en) | 2008-10-24 | 2012-05-29 | Nuance Communications, Inc. | Speaker verification methods and apparatus |
US8644488B2 (en) | 2008-10-27 | 2014-02-04 | Nuance Communications, Inc. | System and method for automatically generating adaptive interaction logs from customer interaction text |
US8645123B2 (en) | 2008-10-27 | 2014-02-04 | Microsoft Corporation | Image-based semantic distance |
US8412529B2 (en) | 2008-10-29 | 2013-04-02 | Verizon Patent And Licensing Inc. | Method and system for enhancing verbal communication sessions |
KR101543221B1 (en) | 2008-10-31 | 2015-08-12 | 에스케이플래닛 주식회사 | - Method Apparatus and System for Providing Muti User-Multi Service |
TWI487385B (en) | 2008-10-31 | 2015-06-01 | Chi Mei Comm Systems Inc | Volume adjusting device and adjusting method of the same |
JP5230358B2 (en) | 2008-10-31 | 2013-07-10 | キヤノン株式会社 | Information search device, information search method, program, and storage medium |
EP2353108A4 (en) | 2008-11-04 | 2018-01-03 | Strossle International AB | Method and system for analyzing text |
US8170966B1 (en) | 2008-11-04 | 2012-05-01 | Bitdefender IPR Management Ltd. | Dynamic streaming message clustering for rapid spam-wave detection |
US8122094B1 (en) | 2008-11-05 | 2012-02-21 | Kotab Dominic M | Methods for performing an action relating to the scheduling of an event by performing one or more actions based on a response to a message |
US8122353B2 (en) | 2008-11-07 | 2012-02-21 | Yahoo! Inc. | Composing a message in an online textbox using a non-latin script |
JP5538415B2 (en) | 2008-11-10 | 2014-07-02 | グーグル・インコーポレーテッド | Multi-sensory voice detection |
KR20100053149A (en) | 2008-11-12 | 2010-05-20 | 삼성전자주식회사 | Apparatus and method for scheduling considering each attendees' context in mobile communicatiion terminal |
US8249870B2 (en) | 2008-11-12 | 2012-08-21 | Massachusetts Institute Of Technology | Semi-automatic speech transcription |
US8386261B2 (en) | 2008-11-14 | 2013-02-26 | Vocollect Healthcare Systems, Inc. | Training/coaching system for a voice-enabled work environment |
US8832319B2 (en) | 2008-11-18 | 2014-09-09 | Amazon Technologies, Inc. | Synchronization of digital content |
US8108214B2 (en) | 2008-11-19 | 2012-01-31 | Robert Bosch Gmbh | System and method for recognizing proper names in dialog systems |
US8584031B2 (en) | 2008-11-19 | 2013-11-12 | Apple Inc. | Portable touch screen device, method, and graphical user interface for using emoji characters |
US8296124B1 (en) | 2008-11-21 | 2012-10-23 | Google Inc. | Method and apparatus for detecting incorrectly translated text in a document |
US9202455B2 (en) | 2008-11-24 | 2015-12-01 | Qualcomm Incorporated | Systems, methods, apparatus, and computer program products for enhanced active noise cancellation |
US20100128701A1 (en) | 2008-11-24 | 2010-05-27 | Qualcomm Incorporated | Beacon transmission for participation in peer-to-peer formation and discovery |
US20100131265A1 (en) | 2008-11-25 | 2010-05-27 | Nokia Corporation | Method, Apparatus and Computer Program Product for Providing Context Aware Queries in a Network |
US20100131498A1 (en) | 2008-11-26 | 2010-05-27 | General Electric Company | Automated healthcare information composition and query enhancement |
US8442824B2 (en) | 2008-11-26 | 2013-05-14 | Nuance Communications, Inc. | Device, system, and method of liveness detection utilizing voice biometrics |
US8140328B2 (en) | 2008-12-01 | 2012-03-20 | At&T Intellectual Property I, L.P. | User intention based on N-best list of recognition hypotheses for utterances in a dialog |
US20100138680A1 (en) | 2008-12-02 | 2010-06-03 | At&T Mobility Ii Llc | Automatic display and voice command activation with hand edge sensing |
US8489599B2 (en) | 2008-12-02 | 2013-07-16 | Palo Alto Research Center Incorporated | Context and activity-driven content delivery and interaction |
US8117036B2 (en) | 2008-12-03 | 2012-02-14 | At&T Intellectual Property I, L.P. | Non-disruptive side conversation information retrieval |
US8073693B2 (en) | 2008-12-04 | 2011-12-06 | At&T Intellectual Property I, L.P. | System and method for pronunciation modeling |
JP5257311B2 (en) | 2008-12-05 | 2013-08-07 | ソニー株式会社 | Information processing apparatus and information processing method |
US8589157B2 (en) | 2008-12-05 | 2013-11-19 | Microsoft Corporation | Replying to text messages via automated voice search techniques |
US8054180B1 (en) | 2008-12-08 | 2011-11-08 | Amazon Technologies, Inc. | Location aware reminders |
US20100185949A1 (en) | 2008-12-09 | 2010-07-22 | Denny Jaeger | Method for using gesture objects for computer control |
EP2196989B1 (en) | 2008-12-10 | 2012-06-27 | Nuance Communications, Inc. | Grammar and template-based speech recognition of spoken utterances |
WO2010067118A1 (en) | 2008-12-11 | 2010-06-17 | Novauris Technologies Limited | Speech recognition involving a mobile device |
US20100153448A1 (en) | 2008-12-12 | 2010-06-17 | International Business Machines Corporation | Persistent search notification |
US8121842B2 (en) | 2008-12-12 | 2012-02-21 | Microsoft Corporation | Audio output of a document from mobile device |
US8160881B2 (en) | 2008-12-15 | 2012-04-17 | Microsoft Corporation | Human-assisted pronunciation generation |
US8208609B2 (en) | 2008-12-15 | 2012-06-26 | Centurylink Intellectual Property Llc | System and method for voice activated dialing from a home phone |
DE112009003645B4 (en) | 2008-12-16 | 2014-05-15 | Mitsubishi Electric Corporation | navigation device |
US8799495B2 (en) | 2008-12-17 | 2014-08-05 | At&T Intellectual Property I, Lp | Multiple devices multimedia control |
US8447588B2 (en) | 2008-12-18 | 2013-05-21 | Palo Alto Research Center Incorporated | Region-matching transducers for natural language processing |
JP5329939B2 (en) | 2008-12-19 | 2013-10-30 | Kddi株式会社 | Context search method and apparatus |
US9323854B2 (en) | 2008-12-19 | 2016-04-26 | Intel Corporation | Method, apparatus and system for location assisted translation |
EP2368199B1 (en) | 2008-12-22 | 2018-10-31 | Google LLC | Asynchronous distributed de-duplication for replicated content addressable storage clusters |
US8635068B2 (en) | 2008-12-23 | 2014-01-21 | At&T Intellectual Property I, L.P. | System and method for recognizing speech with dialect grammars |
JP5326892B2 (en) | 2008-12-26 | 2013-10-30 | 富士通株式会社 | Information processing apparatus, program, and method for generating acoustic model |
US9059991B2 (en) | 2008-12-31 | 2015-06-16 | Bce Inc. | System and method for unlocking a device |
US8456420B2 (en) | 2008-12-31 | 2013-06-04 | Intel Corporation | Audible list traversal |
US8447609B2 (en) | 2008-12-31 | 2013-05-21 | Intel Corporation | Adjustment of temporal acoustical characteristics |
KR101543326B1 (en) | 2009-01-05 | 2015-08-10 | 삼성전자주식회사 | System on chip and driving method thereof |
TW201027515A (en) | 2009-01-06 | 2010-07-16 | High Tech Comp Corp | Electronic event-recording device and method thereof |
EP2205010A1 (en) | 2009-01-06 | 2010-07-07 | BRITISH TELECOMMUNICATIONS public limited company | Messaging |
US8332205B2 (en) | 2009-01-09 | 2012-12-11 | Microsoft Corporation | Mining transliterations for out-of-vocabulary query terms |
US20100180218A1 (en) | 2009-01-15 | 2010-07-15 | International Business Machines Corporation | Editing metadata in a social network |
US8498866B2 (en) | 2009-01-15 | 2013-07-30 | K-Nfb Reading Technology, Inc. | Systems and methods for multiple language document narration |
US10088976B2 (en) | 2009-01-15 | 2018-10-02 | Em Acquisition Corp., Inc. | Systems and methods for multiple voice document narration |
JP2010166478A (en) | 2009-01-19 | 2010-07-29 | Hitachi Kokusai Electric Inc | Radio communication terminal |
EP2211336B1 (en) | 2009-01-23 | 2014-10-08 | Harman Becker Automotive Systems GmbH | Improved speech input using navigation information |
US8213911B2 (en) | 2009-01-28 | 2012-07-03 | Virtual Hold Technology Llc | Mobile communication device for establishing automated call back |
US8200489B1 (en) | 2009-01-29 | 2012-06-12 | The United States Of America As Represented By The Secretary Of The Navy | Multi-resolution hidden markov model using class specific features |
US8463806B2 (en) | 2009-01-30 | 2013-06-11 | Lexisnexis | Methods and systems for creating and using an adaptive thesaurus |
US9070282B2 (en) | 2009-01-30 | 2015-06-30 | Altorr Corp. | Smartphone control of electrical devices |
US20100197359A1 (en) | 2009-01-30 | 2010-08-05 | Harris Technology, Llc | Automatic Detection of Wireless Phone |
US8862252B2 (en) | 2009-01-30 | 2014-10-14 | Apple Inc. | Audio user interface for displayless electronic device |
US20110307491A1 (en) | 2009-02-04 | 2011-12-15 | Fisk Charles M | Digital photo organizing and tagging method |
US9489131B2 (en) | 2009-02-05 | 2016-11-08 | Apple Inc. | Method of presenting a web page for accessibility browsing |
US8254972B2 (en) | 2009-02-13 | 2012-08-28 | Sony Mobile Communications Ab | Device and method for handling messages |
US8428758B2 (en) | 2009-02-16 | 2013-04-23 | Apple Inc. | Dynamic audio ducking |
US8032602B2 (en) | 2009-02-18 | 2011-10-04 | International Business Machines Corporation | Prioritization of recipient email messages |
DE202010018601U1 (en) | 2009-02-18 | 2018-04-30 | Google LLC (n.d.Ges.d. Staates Delaware) | Automatically collecting information, such as gathering information using a document recognizing device |
US8326637B2 (en) | 2009-02-20 | 2012-12-04 | Voicebox Technologies, Inc. | System and method for processing multi-modal device interactions in a natural language voice services environment |
CA2753576A1 (en) | 2009-02-25 | 2010-09-02 | Miri Systems, Llc | Payment system and method |
ATE544291T1 (en) | 2009-02-27 | 2012-02-15 | Research In Motion Ltd | MOBILE RADIO COMMUNICATION DEVICE WITH SPEECH TO TEXT CONVERSION AND ASSOCIATED METHODS |
US8155630B2 (en) | 2009-02-27 | 2012-04-10 | Research In Motion Limited | Communications system providing mobile device notification based upon personal interest information and calendar events |
US9646603B2 (en) | 2009-02-27 | 2017-05-09 | Longsand Limited | Various apparatus and methods for a speech recognition system |
US9280971B2 (en) | 2009-02-27 | 2016-03-08 | Blackberry Limited | Mobile wireless communications device with speech to text conversion and related methods |
US20100223131A1 (en) | 2009-02-27 | 2010-09-02 | Research In Motion Limited | Communications system providing mobile device notification based upon contact web pages and related methods |
KR101041039B1 (en) | 2009-02-27 | 2011-06-14 | 고려대학교 산학협력단 | Method and Apparatus for space-time voice activity detection using audio and video information |
US8280434B2 (en) | 2009-02-27 | 2012-10-02 | Research In Motion Limited | Mobile wireless communications device for hearing and/or speech impaired user |
US9171284B2 (en) | 2009-03-02 | 2015-10-27 | Microsoft Technology Licensing, Llc | Techniques to restore communications sessions for applications having conversation and meeting environments |
CN102341843B (en) | 2009-03-03 | 2014-01-29 | 三菱电机株式会社 | Voice recognition device |
US8239333B2 (en) | 2009-03-03 | 2012-08-07 | Microsoft Corporation | Media tag recommendation technologies |
US20100229100A1 (en) | 2009-03-03 | 2010-09-09 | Sprint Spectrum L.P. | Methods and Systems for Storing and Accessing Application History |
JP2010205111A (en) | 2009-03-05 | 2010-09-16 | Nippon Telegr & Teleph Corp <Ntt> | System, and method for reproducing context, first terminal device, second terminal device, context obtaining device or storage device, program thereof |
US8805439B2 (en) | 2009-03-05 | 2014-08-12 | Lg Electronics Inc. | Mobile terminal and method for controlling the same |
US8605039B2 (en) | 2009-03-06 | 2013-12-10 | Zimpl Ab | Text input |
JP5138810B2 (en) | 2009-03-06 | 2013-02-06 | シャープ株式会社 | Bookmark using device, bookmark creating device, bookmark sharing system, control method, control program, and recording medium |
US20100225809A1 (en) | 2009-03-09 | 2010-09-09 | Sony Corporation And Sony Electronics Inc. | Electronic book with enhanced features |
US8380507B2 (en) | 2009-03-09 | 2013-02-19 | Apple Inc. | Systems and methods for determining the language to use for speech generated by a text to speech engine |
US8165321B2 (en) | 2009-03-10 | 2012-04-24 | Apple Inc. | Intelligent clip mixing |
CN102349087B (en) | 2009-03-12 | 2015-05-06 | 谷歌公司 | Automatically providing content associated with captured information, such as information captured in real-time |
CN101833286A (en) | 2009-03-13 | 2010-09-15 | 王俊锋 | Intelligent home controller |
US8417526B2 (en) | 2009-03-13 | 2013-04-09 | Adacel, Inc. | Speech recognition learning system and method |
US8286106B2 (en) | 2009-03-13 | 2012-10-09 | Oracle America, Inc. | System and method for interacting with status information on a touch screen device |
US20100235780A1 (en) | 2009-03-16 | 2010-09-16 | Westerman Wayne C | System and Method for Identifying Words Based on a Sequence of Keyboard Events |
US8255830B2 (en) | 2009-03-16 | 2012-08-28 | Apple Inc. | Methods and graphical user interfaces for editing on a multifunction device with a touch screen display |
CN101515952B (en) | 2009-03-18 | 2011-04-27 | 南京邮电大学 | Multi-sensor mobile phone |
CN102439540B (en) | 2009-03-19 | 2015-04-08 | 谷歌股份有限公司 | Input method editor |
JP2010224194A (en) | 2009-03-23 | 2010-10-07 | Sony Corp | Speech recognition device and speech recognition method, language model generating device and language model generating method, and computer program |
JP5419136B2 (en) | 2009-03-24 | 2014-02-19 | アルパイン株式会社 | Audio output device |
KR101078864B1 (en) | 2009-03-26 | 2011-11-02 | 한국과학기술원 | The query/document topic category transition analysis system and method and the query expansion based information retrieval system and method |
US20100250599A1 (en) | 2009-03-30 | 2010-09-30 | Nokia Corporation | Method and apparatus for integration of community-provided place data |
GB201016385D0 (en) | 2010-09-29 | 2010-11-10 | Touchtype Ltd | System and method for inputting text into electronic devices |
GB0905457D0 (en) | 2009-03-30 | 2009-05-13 | Touchtype Ltd | System and method for inputting text into electronic devices |
US9424246B2 (en) | 2009-03-30 | 2016-08-23 | Touchtype Ltd. | System and method for inputting text into electronic devices |
US9189472B2 (en) | 2009-03-30 | 2015-11-17 | Touchtype Limited | System and method for inputting text into small screen devices |
US10191654B2 (en) | 2009-03-30 | 2019-01-29 | Touchtype Limited | System and method for inputting text into electronic devices |
US8798255B2 (en) | 2009-03-31 | 2014-08-05 | Nice Systems Ltd | Methods and apparatus for deep interaction analysis |
US8539382B2 (en) | 2009-04-03 | 2013-09-17 | Palm, Inc. | Preventing unintentional activation and/or input in an electronic device |
US20100263015A1 (en) | 2009-04-09 | 2010-10-14 | Verizon Patent And Licensing Inc. | Wireless Interface for Set Top Box |
US8166032B2 (en) | 2009-04-09 | 2012-04-24 | MarketChorus, Inc. | System and method for sentiment-based text classification and relevancy ranking |
US8805823B2 (en) | 2009-04-14 | 2014-08-12 | Sri International | Content processing systems and methods |
KR101537706B1 (en) | 2009-04-16 | 2015-07-20 | 엘지전자 주식회사 | Mobile terminal and control method thereof |
US8209174B2 (en) | 2009-04-17 | 2012-06-26 | Saudi Arabian Oil Company | Speaker verification system |
US20110065456A1 (en) | 2009-04-20 | 2011-03-17 | Brennan Joseph P | Cellular device deactivation system |
US9761219B2 (en) | 2009-04-21 | 2017-09-12 | Creative Technology Ltd | System and method for distributed text-to-speech synthesis and intelligibility |
US8660970B1 (en) | 2009-04-23 | 2014-02-25 | The Boeing Company | Passive learning and autonomously interactive system for leveraging user knowledge in networked environments |
CN102405463B (en) | 2009-04-30 | 2015-07-29 | 三星电子株式会社 | Utilize the user view reasoning device and method of multi-modal information |
KR101032792B1 (en) | 2009-04-30 | 2011-05-06 | 주식회사 코오롱 | Polyester fabric for airbag and manufacturing method thereof |
KR101581883B1 (en) | 2009-04-30 | 2016-01-11 | 삼성전자주식회사 | Appratus for detecting voice using motion information and method thereof |
WO2010129939A1 (en) | 2009-05-08 | 2010-11-11 | Obdedge, Llc | Systems, methods, and devices for policy-based control and monitoring of use of mobile devices by vehicle operators |
US9298823B2 (en) | 2009-05-08 | 2016-03-29 | International Business Machines Corporation | Identifying core content based on citations |
WO2010131256A1 (en) | 2009-05-13 | 2010-11-18 | Rajesh Mehra | A keyboard for linguistic scripts |
US20100293460A1 (en) | 2009-05-14 | 2010-11-18 | Budelli Joe G | Text selection method and system based on gestures |
US8583511B2 (en) | 2009-05-19 | 2013-11-12 | Bradley Marshall Hendrickson | Systems and methods for storing customer purchasing and preference data and enabling a customer to pre-register orders and events |
US8498857B2 (en) | 2009-05-19 | 2013-07-30 | Tata Consultancy Services Limited | System and method for rapid prototyping of existing speech recognition solutions in different languages |
KR101577607B1 (en) | 2009-05-22 | 2015-12-15 | 삼성전자주식회사 | Apparatus and method for language expression using context and intent awareness |
WO2010138775A1 (en) | 2009-05-27 | 2010-12-02 | Geodelic, Inc. | Location discovery system and method |
US8577543B2 (en) | 2009-05-28 | 2013-11-05 | Intelligent Mechatronic Systems Inc. | Communication system with personal information management and remote vehicle monitoring and control features |
US8369822B2 (en) | 2009-05-28 | 2013-02-05 | At&T Intellectual Property I, Lp | Systems and methods for providing emergency callback procedures |
US20150294377A1 (en) | 2009-05-30 | 2015-10-15 | Edmond K. Chow | Trust network effect |
US20120310652A1 (en) | 2009-06-01 | 2012-12-06 | O'sullivan Daniel | Adaptive Human Computer Interface (AAHCI) |
US8095119B2 (en) | 2009-06-02 | 2012-01-10 | Microsoft Corporation | In-call contact information display |
EP2259252B1 (en) | 2009-06-02 | 2012-08-01 | Nuance Communications, Inc. | Speech recognition method for selecting a combination of list elements via a speech input |
US10241644B2 (en) | 2011-06-03 | 2019-03-26 | Apple Inc. | Actionable reminder entries |
US8560313B2 (en) | 2010-05-13 | 2013-10-15 | General Motors Llc | Transient noise rejection for speech recognition |
US10540976B2 (en) | 2009-06-05 | 2020-01-21 | Apple Inc. | Contextual voice commands |
US10241752B2 (en) | 2011-09-30 | 2019-03-26 | Apple Inc. | Interface for a virtual digital assistant |
US9858925B2 (en) | 2009-06-05 | 2018-01-02 | Apple Inc. | Using context information to facilitate processing of commands in a virtual assistant |
US10255566B2 (en) | 2011-06-03 | 2019-04-09 | Apple Inc. | Generating and processing task items that represent tasks to perform |
US20120327009A1 (en) | 2009-06-07 | 2012-12-27 | Apple Inc. | Devices, methods, and graphical user interfaces for accessibility using a touch-sensitive surface |
KR101562792B1 (en) | 2009-06-10 | 2015-10-23 | 삼성전자주식회사 | Apparatus and method for providing goal predictive interface |
US8412531B2 (en) | 2009-06-10 | 2013-04-02 | Microsoft Corporation | Touch anywhere to speak |
JP2010287063A (en) | 2009-06-11 | 2010-12-24 | Zenrin Datacom Co Ltd | Information provision device, information provision system and program |
US20130219333A1 (en) | 2009-06-12 | 2013-08-22 | Adobe Systems Incorporated | Extensible Framework for Facilitating Interaction with Devices |
US8290777B1 (en) | 2009-06-12 | 2012-10-16 | Amazon Technologies, Inc. | Synchronizing the playing and displaying of digital content |
US8484027B1 (en) | 2009-06-12 | 2013-07-09 | Skyreader Media Inc. | Method for live remote narration of a digital book |
US20100317371A1 (en) | 2009-06-12 | 2010-12-16 | Westerinen William J | Context-based interaction model for mobile devices |
US8306238B2 (en) | 2009-06-17 | 2012-11-06 | Sony Ericsson Mobile Communications Ab | Method and circuit for controlling an output of an audio signal of a battery-powered device |
US8533622B2 (en) | 2009-06-17 | 2013-09-10 | Microsoft Corporation | Integrating digital book and zoom interface displays |
US20100325140A1 (en) * | 2009-06-18 | 2010-12-23 | Verizon Patent And Licensing Inc. | System for and method of parallel searching |
US20100324709A1 (en) | 2009-06-22 | 2010-12-23 | Tree Of Life Publishing | E-book reader with voice annotation |
US10353967B2 (en) | 2009-06-22 | 2019-07-16 | Microsoft Technology Licensing, Llc | Assigning relevance weights based on temporal dynamics |
US9215212B2 (en) | 2009-06-22 | 2015-12-15 | Citrix Systems, Inc. | Systems and methods for providing a visualizer for rules of an application firewall |
US11012732B2 (en) | 2009-06-25 | 2021-05-18 | DISH Technologies L.L.C. | Voice enabled media presentation systems and methods |
US20100330908A1 (en) | 2009-06-25 | 2010-12-30 | Blueant Wireless Pty Limited | Telecommunications device with voice-controlled functions |
US20100332236A1 (en) | 2009-06-25 | 2010-12-30 | Blueant Wireless Pty Limited | Voice-triggered operation of electronic devices |
US9754224B2 (en) | 2009-06-26 | 2017-09-05 | International Business Machines Corporation | Action based to-do list |
US8983640B2 (en) | 2009-06-26 | 2015-03-17 | Intel Corporation | Controlling audio players using environmental audio analysis |
US8219930B2 (en) | 2009-06-26 | 2012-07-10 | Verizon Patent And Licensing Inc. | Radial menu display systems and methods |
US8527278B2 (en) | 2009-06-29 | 2013-09-03 | Abraham Ben David | Intelligent home automation |
US20100332224A1 (en) | 2009-06-30 | 2010-12-30 | Nokia Corporation | Method and apparatus for converting text to audio and tactile output |
US9431006B2 (en) | 2009-07-02 | 2016-08-30 | Apple Inc. | Methods and apparatuses for automatic speech recognition |
US20110002487A1 (en) | 2009-07-06 | 2011-01-06 | Apple Inc. | Audio Channel Assignment for Audio Output in a Movable Device |
US8700399B2 (en) | 2009-07-06 | 2014-04-15 | Sensory, Inc. | Systems and methods for hands-free voice control and voice search |
US8943423B2 (en) | 2009-07-07 | 2015-01-27 | International Business Machines Corporation | User interface indicators for changed user interface elements |
KR101083540B1 (en) | 2009-07-08 | 2011-11-14 | 엔에이치엔(주) | System and method for transforming vernacular pronunciation with respect to hanja using statistical method |
US8344847B2 (en) | 2009-07-09 | 2013-01-01 | Medtronic Minimed, Inc. | Coordination of control commands in a medical device system having at least one therapy delivery device and at least one wireless controller device |
EP2454733A1 (en) | 2009-07-15 | 2012-05-23 | Google, Inc. | Commands directed at displayed text |
US8892439B2 (en) | 2009-07-15 | 2014-11-18 | Microsoft Corporation | Combination and federation of local and remote speech recognition |
US20110016150A1 (en) | 2009-07-20 | 2011-01-20 | Engstroem Jimmy | System and method for tagging multiple digital images |
US20110016421A1 (en) | 2009-07-20 | 2011-01-20 | Microsoft Corporation | Task oriented user interface platform |
US8213962B2 (en) | 2009-07-21 | 2012-07-03 | Verizon Patent And Licensing Inc. | Vehicle computer link to mobile phone |
US7953679B2 (en) | 2009-07-22 | 2011-05-31 | Xerox Corporation | Scalable indexing for layout based document retrieval and ranking |
WO2011011025A1 (en) | 2009-07-24 | 2011-01-27 | Research In Motion Limited | Method and apparatus for a touch-sensitive display |
US8239129B2 (en) | 2009-07-27 | 2012-08-07 | Robert Bosch Gmbh | Method and system for improving speech recognition accuracy by use of geographic information |
US9489577B2 (en) | 2009-07-27 | 2016-11-08 | Cxense Asa | Visual similarity for video content |
US9117448B2 (en) | 2009-07-27 | 2015-08-25 | Cisco Technology, Inc. | Method and system for speech recognition using social networks |
US20110029616A1 (en) | 2009-07-29 | 2011-02-03 | Guanming Wang | Unified auto-reply to an email coming from unified messaging service |
US8875219B2 (en) | 2009-07-30 | 2014-10-28 | Blackberry Limited | Apparatus and method for controlled sharing of personal information |
JP2011033874A (en) | 2009-08-03 | 2011-02-17 | Alpine Electronics Inc | Device for multilingual voice recognition, multilingual voice recognition dictionary creation method |
US8340312B2 (en) | 2009-08-04 | 2012-12-25 | Apple Inc. | Differential mode noise cancellation with active real-time control for microphone-speaker combinations used in two way audio communications |
US8160877B1 (en) | 2009-08-06 | 2012-04-17 | Narus, Inc. | Hierarchical real-time speaker recognition for biometric VoIP verification and targeting |
US20110047072A1 (en) | 2009-08-07 | 2011-02-24 | Visa U.S.A. Inc. | Systems and Methods for Propensity Analysis and Validation |
US8233919B2 (en) | 2009-08-09 | 2012-07-31 | Hntb Holdings Ltd. | Intelligently providing user-specific transportation-related information |
JP5201599B2 (en) | 2009-08-11 | 2013-06-05 | Necカシオモバイルコミュニケーションズ株式会社 | Terminal device and program |
US20110040707A1 (en) | 2009-08-12 | 2011-02-17 | Ford Global Technologies, Llc | Intelligent music selection in vehicles |
US8768313B2 (en) | 2009-08-17 | 2014-07-01 | Digimarc Corporation | Methods and systems for image or audio recognition processing |
US8626133B2 (en) | 2009-08-19 | 2014-01-07 | Cisco Technology, Inc. | Matching a location of a contact with a task location |
US8654952B2 (en) | 2009-08-20 | 2014-02-18 | T-Mobile Usa, Inc. | Shareable applications on telecommunications devices |
KR101496649B1 (en) | 2009-08-21 | 2015-03-02 | 삼성전자주식회사 | Method and apparatus for sharing fuction of external device |
EP2341450A1 (en) | 2009-08-21 | 2011-07-06 | Mikko Kalervo Väänänen | Method and means for data searching and language translation |
US9277021B2 (en) | 2009-08-21 | 2016-03-01 | Avaya Inc. | Sending a user associated telecommunication address |
JP2011045005A (en) | 2009-08-24 | 2011-03-03 | Fujitsu Toshiba Mobile Communications Ltd | Cellular phone |
SG178344A1 (en) | 2009-08-25 | 2012-03-29 | Univ Nanyang Tech | A method and system for reconstructing speech from an input signal comprising whispers |
US20110054647A1 (en) | 2009-08-26 | 2011-03-03 | Nokia Corporation | Network service for an audio interface unit |
JP2011048671A (en) | 2009-08-27 | 2011-03-10 | Kyocera Corp | Input device and control method of input device |
CN101996631B (en) | 2009-08-28 | 2014-12-03 | 国际商业机器公司 | Method and device for aligning texts |
US20110238407A1 (en) | 2009-08-31 | 2011-09-29 | O3 Technologies, Llc | Systems and methods for speech-to-speech translation |
US8451238B2 (en) | 2009-09-02 | 2013-05-28 | Amazon Technologies, Inc. | Touch-screen user interface |
EP2473916A4 (en) | 2009-09-02 | 2013-07-10 | Stanford Res Inst Int | Method and apparatus for exploiting human feedback in an intelligent automated assistant |
US8624851B2 (en) | 2009-09-02 | 2014-01-07 | Amazon Technologies, Inc. | Touch-screen user interface |
TW201110108A (en) | 2009-09-04 | 2011-03-16 | Chunghwa Telecom Co Ltd | Voice noise elimination method for microphone array |
WO2011026247A1 (en) | 2009-09-04 | 2011-03-10 | Svox Ag | Speech enhancement techniques on the power spectrum |
US8675084B2 (en) | 2009-09-04 | 2014-03-18 | Apple Inc. | Systems and methods for remote camera control |
US20120265535A1 (en) | 2009-09-07 | 2012-10-18 | Donald Ray Bryant-Rich | Personal voice operated reminder system |
US8560300B2 (en) | 2009-09-09 | 2013-10-15 | International Business Machines Corporation | Error correction using fact repositories |
US20110060812A1 (en) | 2009-09-10 | 2011-03-10 | Level 3 Communications, Llc | Cache server with extensible programming framework |
US8788267B2 (en) | 2009-09-10 | 2014-07-22 | Mitsubishi Electric Research Laboratories, Inc. | Multi-purpose contextual control |
US8321527B2 (en) | 2009-09-10 | 2012-11-27 | Tribal Brands | System and method for tracking user location and associated activity and responsively providing mobile device updates |
US9140569B2 (en) | 2009-09-11 | 2015-09-22 | Telenav, Inc | Location based system with contextual contact manager mechanism and method of operation thereof |
US20110066468A1 (en) | 2009-09-11 | 2011-03-17 | Internationl Business Machines Corporation | Dynamic event planning through location awareness |
US8510769B2 (en) * | 2009-09-14 | 2013-08-13 | Tivo Inc. | Media content finger print system |
US10587833B2 (en) | 2009-09-16 | 2020-03-10 | Disney Enterprises, Inc. | System and method for automated network search and companion display of result relating to audio-video metadata |
US9015148B2 (en) | 2009-09-21 | 2015-04-21 | Microsoft Corporation | Suggesting related search queries during web browsing |
US8972878B2 (en) | 2009-09-21 | 2015-03-03 | Avaya Inc. | Screen icon manipulation by context and frequency of Use |
US8312079B2 (en) * | 2009-09-22 | 2012-11-13 | Thwapr, Inc. | Adaptive rendering for mobile media sharing |
US8768308B2 (en) | 2009-09-29 | 2014-07-01 | Deutsche Telekom Ag | Apparatus and method for creating and managing personal schedules via context-sensing and actuation |
US9111538B2 (en) | 2009-09-30 | 2015-08-18 | T-Mobile Usa, Inc. | Genius button secondary commands |
TW201113741A (en) | 2009-10-01 | 2011-04-16 | Htc Corp | Lock-state switching method, electronic apparatus and computer program product |
KR20110036385A (en) | 2009-10-01 | 2011-04-07 | 삼성전자주식회사 | Apparatus for analyzing intention of user and method thereof |
US9338274B2 (en) | 2009-10-02 | 2016-05-10 | Blackberry Limited | Method of interacting with electronic devices in a locked state and handheld electronic device configured to permit interaction when in a locked state |
US20110083079A1 (en) | 2009-10-02 | 2011-04-07 | International Business Machines Corporation | Apparatus, system, and method for improved type-ahead functionality in a type-ahead field based on activity of a user within a user interface |
JP5473520B2 (en) | 2009-10-06 | 2014-04-16 | キヤノン株式会社 | Input device and control method thereof |
US7809550B1 (en) | 2009-10-08 | 2010-10-05 | Joan Barry Barrows | System for reading chinese characters in seconds |
US20110087685A1 (en) | 2009-10-09 | 2011-04-14 | Microsoft Corporation | Location-based service middleware |
CN101673544B (en) | 2009-10-10 | 2012-07-04 | 上海电虹软件有限公司 | Cross monitoring method and system based on voiceprint recognition and location tracking |
US8335689B2 (en) | 2009-10-14 | 2012-12-18 | Cogi, Inc. | Method and system for efficient management of speech transcribers |
US8611876B2 (en) | 2009-10-15 | 2013-12-17 | Larry Miller | Configurable phone with interactive voice response engine |
US8510103B2 (en) | 2009-10-15 | 2013-08-13 | Paul Angott | System and method for voice recognition |
US8255217B2 (en) | 2009-10-16 | 2012-08-28 | At&T Intellectual Property I, Lp | Systems and methods for creating and using geo-centric language models |
US8451112B2 (en) | 2009-10-19 | 2013-05-28 | Qualcomm Incorporated | Methods and apparatus for estimating departure time based on known calendar events |
US8332748B1 (en) | 2009-10-22 | 2012-12-11 | Google Inc. | Multi-directional auto-complete menu |
US8554537B2 (en) | 2009-10-23 | 2013-10-08 | Samsung Electronics Co., Ltd | Method and device for transliteration |
US8326624B2 (en) | 2009-10-26 | 2012-12-04 | International Business Machines Corporation | Detecting and communicating biometrics of recorded voice during transcription process |
US20110099507A1 (en) | 2009-10-28 | 2011-04-28 | Google Inc. | Displaying a collection of interactive elements that trigger actions directed to an item |
US9197736B2 (en) | 2009-12-31 | 2015-11-24 | Digimarc Corporation | Intuitive computing methods and systems |
CA2779289A1 (en) | 2009-10-28 | 2011-05-19 | Google Inc. | Computer-to-computer communication |
US8386574B2 (en) | 2009-10-29 | 2013-02-26 | Xerox Corporation | Multi-modality classification for one-class classification in social networks |
US8315617B2 (en) | 2009-10-31 | 2012-11-20 | Btpatent Llc | Controlling mobile device functions |
US8832205B2 (en) | 2009-11-02 | 2014-09-09 | Lextine Software, Llc | System and method for extracting calendar events from free-form email |
CN102483918B (en) | 2009-11-06 | 2014-08-20 | 株式会社东芝 | Voice recognition device |
US20120137367A1 (en) | 2009-11-06 | 2012-05-31 | Cataphora, Inc. | Continuous anomaly detection based on behavior modeling and heterogeneous information analysis |
CN102056026B (en) | 2009-11-06 | 2013-04-03 | 中国移动通信集团设计院有限公司 | Audio/video synchronization detection method and system, and voice detection method and system |
US8358747B2 (en) | 2009-11-10 | 2013-01-22 | International Business Machines Corporation | Real time automatic caller speech profiling |
KR20120091325A (en) | 2009-11-10 | 2012-08-17 | 둘세타 인코포레이티드 | Dynamic audio playback of soundtracks for electronic visual works |
US8321209B2 (en) | 2009-11-10 | 2012-11-27 | Research In Motion Limited | System and method for low overhead frequency domain voice authentication |
US20110111724A1 (en) | 2009-11-10 | 2011-05-12 | David Baptiste | Method and apparatus for combating distracted driving |
US9502025B2 (en) | 2009-11-10 | 2016-11-22 | Voicebox Technologies Corporation | System and method for providing a natural language content dedication service |
US9171541B2 (en) | 2009-11-10 | 2015-10-27 | Voicebox Technologies Corporation | System and method for hybrid processing in a natural language voice services environment |
US8682649B2 (en) | 2009-11-12 | 2014-03-25 | Apple Inc. | Sentiment prediction from textual data |
US8732180B2 (en) | 2009-11-12 | 2014-05-20 | Apple Inc. | Recommending media items |
CN102860039B (en) | 2009-11-12 | 2016-10-19 | 罗伯特·亨利·弗莱特 | Hands-free phone and/or microphone array and use their method and system |
US8712759B2 (en) | 2009-11-13 | 2014-04-29 | Clausal Computing Oy | Specializing disambiguation of a natural language expression |
US20130166303A1 (en) | 2009-11-13 | 2013-06-27 | Adobe Systems Incorporated | Accessing media data using metadata repository |
KR20110052863A (en) | 2009-11-13 | 2011-05-19 | 삼성전자주식회사 | Mobile device and method for generating control signal thereof |
TWI391915B (en) | 2009-11-17 | 2013-04-01 | Inst Information Industry | Method and apparatus for builiding phonetic variation models and speech recognition |
KR101595029B1 (en) | 2009-11-18 | 2016-02-17 | 엘지전자 주식회사 | Mobile terminal and method for controlling the same |
US8358752B2 (en) | 2009-11-19 | 2013-01-22 | At&T Mobility Ii Llc | User profile based speech to text conversion for visual voice mail |
US8630971B2 (en) | 2009-11-20 | 2014-01-14 | Indian Institute Of Science | System and method of using Multi Pattern Viterbi Algorithm for joint decoding of multiple patterns |
US8358749B2 (en) | 2009-11-21 | 2013-01-22 | At&T Intellectual Property I, L.P. | System and method to search a media content database based on voice input data |
KR101960835B1 (en) | 2009-11-24 | 2019-03-21 | 삼성전자주식회사 | Schedule Management System Using Interactive Robot and Method Thereof |
US20110153330A1 (en) | 2009-11-27 | 2011-06-23 | i-SCROLL | System and method for rendering text synchronized audio |
US8731901B2 (en) | 2009-12-02 | 2014-05-20 | Content Savvy, Inc. | Context aware back-transliteration and translation of names and common phrases using web resources |
CN102741842A (en) | 2009-12-04 | 2012-10-17 | Tivo有限公司 | Multifunction multimedia device |
US8396888B2 (en) | 2009-12-04 | 2013-03-12 | Google Inc. | Location-based searching using a search area that corresponds to a geographical location of a computing device |
US20110137664A1 (en) | 2009-12-09 | 2011-06-09 | International Business Machines Corporation | Providing Schedule Related Information to External Entities |
US8812990B2 (en) | 2009-12-11 | 2014-08-19 | Nokia Corporation | Method and apparatus for presenting a first person world view of content |
KR101622111B1 (en) | 2009-12-11 | 2016-05-18 | 삼성전자 주식회사 | Dialog system and conversational method thereof |
US8224300B2 (en) | 2009-12-11 | 2012-07-17 | Alpine Electronics, Inc. | Method and apparatus to enhance navigation user experience for a smart phone device |
US8543917B2 (en) | 2009-12-11 | 2013-09-24 | Nokia Corporation | Method and apparatus for presenting a first-person world view of content |
US9766089B2 (en) | 2009-12-14 | 2017-09-19 | Nokia Technologies Oy | Method and apparatus for correlating and navigating between a live image and a prerecorded panoramic image |
US20110144857A1 (en) | 2009-12-14 | 2011-06-16 | Theodore Charles Wingrove | Anticipatory and adaptive automobile hmi |
US8892443B2 (en) | 2009-12-15 | 2014-11-18 | At&T Intellectual Property I, L.P. | System and method for combining geographic metadata in automatic speech recognition language and acoustic models |
KR101211796B1 (en) | 2009-12-16 | 2012-12-13 | 포항공과대학교 산학협력단 | Apparatus for foreign language learning and method for providing foreign language learning service |
US8341037B2 (en) * | 2009-12-18 | 2012-12-25 | Apple Inc. | Mixed source media playback |
US20110154193A1 (en) | 2009-12-21 | 2011-06-23 | Nokia Corporation | Method and Apparatus for Text Input |
US9100809B2 (en) | 2009-12-21 | 2015-08-04 | Julia Olincy Olincy | Automatic response option mobile system for responding to incoming texts or calls or both |
US8385982B2 (en) | 2009-12-21 | 2013-02-26 | At&T Intellectual Property I, L.P. | Controlling use of a communications device in accordance with motion of the device |
US8805711B2 (en) | 2009-12-22 | 2014-08-12 | International Business Machines Corporation | Two-layer data architecture for reservation management systems |
KR20110072847A (en) | 2009-12-23 | 2011-06-29 | 삼성전자주식회사 | Dialog management system or method for processing information seeking dialog |
EP3091535B1 (en) | 2009-12-23 | 2023-10-11 | Google LLC | Multi-modal input on an electronic device |
US20110161309A1 (en) | 2009-12-29 | 2011-06-30 | Lx1 Technology Limited | Method Of Sorting The Result Set Of A Search Engine |
US8479107B2 (en) | 2009-12-31 | 2013-07-02 | Nokia Corporation | Method and apparatus for fluid graphical user interface |
US8988356B2 (en) | 2009-12-31 | 2015-03-24 | Google Inc. | Touch sensor and touchscreen user input combination |
US20110166862A1 (en) * | 2010-01-04 | 2011-07-07 | Eyal Eshed | System and method for variable automated response to remote verbal input at a mobile device |
US8494852B2 (en) | 2010-01-05 | 2013-07-23 | Google Inc. | Word-level correction of speech input |
US8600743B2 (en) | 2010-01-06 | 2013-12-03 | Apple Inc. | Noise profile determination for voice-related feature |
WO2011082521A1 (en) | 2010-01-06 | 2011-07-14 | Zoran Corporation | Method and apparatus for voice controlled operation of a media player |
US20110167350A1 (en) | 2010-01-06 | 2011-07-07 | Apple Inc. | Assist Features For Content Display Device |
US8381107B2 (en) | 2010-01-13 | 2013-02-19 | Apple Inc. | Adaptive audio feedback system and method |
US8311838B2 (en) | 2010-01-13 | 2012-11-13 | Apple Inc. | Devices and methods for identifying a prompt corresponding to a voice input in a sequence of prompts |
US8334842B2 (en) | 2010-01-15 | 2012-12-18 | Microsoft Corporation | Recognizing user intent in motion capture system |
US20110179372A1 (en) | 2010-01-15 | 2011-07-21 | Bradford Allen Moore | Automatic Keyboard Layout Determination |
US10276170B2 (en) | 2010-01-18 | 2019-04-30 | Apple Inc. | Intelligent automated assistant |
US10705794B2 (en) | 2010-01-18 | 2020-07-07 | Apple Inc. | Automatically adapting user interfaces for hands-free interaction |
US10553209B2 (en) | 2010-01-18 | 2020-02-04 | Apple Inc. | Systems and methods for hands-free notification summaries |
US10679605B2 (en) | 2010-01-18 | 2020-06-09 | Apple Inc. | Hands-free list-reading by intelligent automated assistant |
US20110179002A1 (en) | 2010-01-19 | 2011-07-21 | Dell Products L.P. | System and Method for a Vector-Space Search Engine |
US8417575B2 (en) * | 2010-01-19 | 2013-04-09 | Apple Inc. | On-device offline purchases using credits |
US8626511B2 (en) | 2010-01-22 | 2014-01-07 | Google Inc. | Multi-dimensional disambiguation of voice commands |
US8301121B2 (en) | 2010-01-22 | 2012-10-30 | Sony Ericsson Mobile Communications Ab | Regulating alerts generated by communication terminals responsive to sensed movement |
US20110184736A1 (en) | 2010-01-26 | 2011-07-28 | Benjamin Slotznick | Automated method of recognizing inputted information items and selecting information items |
US20110184768A1 (en) | 2010-01-27 | 2011-07-28 | Norton Kenneth S | Automatically determine suggested meeting locations based on previously booked calendar events |
JP5633042B2 (en) | 2010-01-28 | 2014-12-03 | 本田技研工業株式会社 | Speech recognition apparatus, speech recognition method, and speech recognition robot |
US8406745B1 (en) | 2010-01-28 | 2013-03-26 | Sprint Communications Company L.P. | Synchronization of voice mail greeting and email auto-reply by a wireless communication device |
US20120330662A1 (en) | 2010-01-29 | 2012-12-27 | Nec Corporation | Input supporting system, method and program |
US8600967B2 (en) | 2010-02-03 | 2013-12-03 | Apple Inc. | Automatic organization of browsing histories |
US8687777B1 (en) | 2010-02-03 | 2014-04-01 | Tal Lavian | Systems and methods for visual presentation and selection of IVR menu |
US8886541B2 (en) | 2010-02-04 | 2014-11-11 | Sony Corporation | Remote controller with position actuatated voice transmission |
US8645287B2 (en) | 2010-02-04 | 2014-02-04 | Microsoft Corporation | Image tagging based upon cross domain context |
US8751218B2 (en) | 2010-02-09 | 2014-06-10 | Siemens Aktiengesellschaft | Indexing content at semantic level |
US8179370B1 (en) | 2010-02-09 | 2012-05-15 | Google Inc. | Proximity based keystroke resolution |
US9413869B2 (en) | 2010-02-10 | 2016-08-09 | Qualcomm Incorporated | Mobile device having plurality of input modes |
US8782556B2 (en) | 2010-02-12 | 2014-07-15 | Microsoft Corporation | User-centric soft keyboard predictive technologies |
US8402018B2 (en) | 2010-02-12 | 2013-03-19 | Korea Advanced Institute Of Science And Technology | Semantic search system using semantic ranking scheme |
US8812056B2 (en) | 2010-02-12 | 2014-08-19 | Christopher D. Higginbotham | Voice-based command driven computer implemented method |
US9965165B2 (en) | 2010-02-19 | 2018-05-08 | Microsoft Technology Licensing, Llc | Multi-finger gestures |
WO2011105996A1 (en) | 2010-02-23 | 2011-09-01 | Hewlett-Packard Development Company, L.P. | Skipping through electronic content on an electronic device |
US9665344B2 (en) | 2010-02-24 | 2017-05-30 | GM Global Technology Operations LLC | Multi-modal input system for a voice-based menu and content navigation service |
US8682667B2 (en) | 2010-02-25 | 2014-03-25 | Apple Inc. | User profiling for selecting user specific voice input processing information |
US9710556B2 (en) | 2010-03-01 | 2017-07-18 | Vcvc Iii Llc | Content recommendation based on collections of entities |
US20120066303A1 (en) | 2010-03-03 | 2012-03-15 | Waldeck Technology, Llc | Synchronized group location updates |
US20110218855A1 (en) | 2010-03-03 | 2011-09-08 | Platformation, Inc. | Offering Promotions Based on Query Analysis |
US8502837B2 (en) | 2010-03-04 | 2013-08-06 | Research In Motion Limited | System and method for activating components on an electronic device using orientation data |
US8903847B2 (en) | 2010-03-05 | 2014-12-02 | International Business Machines Corporation | Digital media voice tags in social networks |
US8948515B2 (en) | 2010-03-08 | 2015-02-03 | Sightera Technologies Ltd. | Method and system for classifying one or more images |
KR101477530B1 (en) | 2010-03-12 | 2014-12-30 | 뉘앙스 커뮤니케이션즈, 인코포레이티드 | Multimodal text input system, such as for use with touch screens on mobile phones |
US8521513B2 (en) | 2010-03-12 | 2013-08-27 | Microsoft Corporation | Localization for interactive voice response systems |
US20110228913A1 (en) | 2010-03-16 | 2011-09-22 | Telcordia Technologies, Inc. | Automatic extraction of information from ongoing voice communication system and methods |
US8374864B2 (en) | 2010-03-17 | 2013-02-12 | Cisco Technology, Inc. | Correlation of transcribed text with corresponding audio |
US20110231218A1 (en) | 2010-03-18 | 2011-09-22 | Tovar Tom C | Systems and Methods for Providing Reminders for a Task List |
CN102893327B (en) | 2010-03-19 | 2015-05-27 | 数字标记公司 | Intuitive computing methods and systems |
US9323756B2 (en) | 2010-03-22 | 2016-04-26 | Lenovo (Singapore) Pte. Ltd. | Audio book and e-book synchronization |
US8554280B2 (en) | 2010-03-23 | 2013-10-08 | Ebay Inc. | Free-form entries during payment processes |
US20110239111A1 (en) | 2010-03-24 | 2011-09-29 | Avaya Inc. | Spell checker interface |
US20110238676A1 (en) | 2010-03-25 | 2011-09-29 | Palm, Inc. | System and method for data capture, storage, and retrieval |
US20110238412A1 (en) | 2010-03-26 | 2011-09-29 | Antoine Ezzat | Method for Constructing Pronunciation Dictionaries |
WO2011119168A1 (en) | 2010-03-26 | 2011-09-29 | Nuance Communications, Inc. | Context based voice activity detection sensitivity |
US9378202B2 (en) | 2010-03-26 | 2016-06-28 | Virtuoz Sa | Semantic clustering |
US8428759B2 (en) | 2010-03-26 | 2013-04-23 | Google Inc. | Predictive pre-recording of audio for voice input |
US8930176B2 (en) | 2010-04-01 | 2015-01-06 | Microsoft Corporation | Interactive multilingual word-alignment techniques |
US8296380B1 (en) | 2010-04-01 | 2012-10-23 | Kel & Partners LLC | Social media based messaging systems and methods |
US20110242007A1 (en) | 2010-04-01 | 2011-10-06 | Gray Theodore W | E-Book with User-Manipulatable Graphical Objects |
WO2011127242A2 (en) | 2010-04-07 | 2011-10-13 | Max Value Solutions INTL, LLC | Method and system for name pronunciation guide services |
US8448084B2 (en) | 2010-04-08 | 2013-05-21 | Twitter, Inc. | User interface mechanics |
US8810684B2 (en) | 2010-04-09 | 2014-08-19 | Apple Inc. | Tagging images in a mobile communications device using a contacts list |
KR101369810B1 (en) | 2010-04-09 | 2014-03-05 | 이초강 | Empirical Context Aware Computing Method For Robot |
CN102214187B (en) | 2010-04-12 | 2017-03-01 | 阿里巴巴集团控股有限公司 | Complex event processing method and device |
CN103080873B (en) | 2010-04-12 | 2016-10-05 | 谷歌公司 | Expansion subrack for Input Method Editor |
JP5315289B2 (en) | 2010-04-12 | 2013-10-16 | トヨタ自動車株式会社 | Operating system and operating method |
US8140567B2 (en) | 2010-04-13 | 2012-03-20 | Microsoft Corporation | Measuring entity extraction complexity |
US8265928B2 (en) | 2010-04-14 | 2012-09-11 | Google Inc. | Geotagged environmental audio for enhanced speech recognition accuracy |
US8756233B2 (en) | 2010-04-16 | 2014-06-17 | Video Semantics | Semantic segmentation and tagging engine |
US8595014B2 (en) | 2010-04-19 | 2013-11-26 | Qualcomm Incorporated | Providing audible navigation system direction updates during predetermined time windows so as to minimize impact on conversations |
WO2011133543A1 (en) | 2010-04-21 | 2011-10-27 | Proteus Biomedical, Inc. | Diagnostic system and method |
US20110260829A1 (en) | 2010-04-21 | 2011-10-27 | Research In Motion Limited | Method of providing security on a portable electronic device having a touch-sensitive display |
US20110264495A1 (en) | 2010-04-22 | 2011-10-27 | Apple Inc. | Aggregation of tagged media item information |
US20110264999A1 (en) | 2010-04-23 | 2011-10-27 | Research In Motion Limited | Electronic device including touch-sensitive input device and method of controlling same |
US20110264530A1 (en) * | 2010-04-23 | 2011-10-27 | Bryan Santangelo | Apparatus and methods for dynamic secondary content and data insertion and delivery |
US8452037B2 (en) | 2010-05-05 | 2013-05-28 | Apple Inc. | Speaker clip |
US8380504B1 (en) | 2010-05-06 | 2013-02-19 | Sprint Communications Company L.P. | Generation of voice profiles |
US8756571B2 (en) | 2010-05-07 | 2014-06-17 | Hewlett-Packard Development Company, L.P. | Natural language text instructions |
US8938436B2 (en) | 2010-05-10 | 2015-01-20 | Verizon Patent And Licensing Inc. | System for and method of providing reusable software service information based on natural language queries |
JP2011238022A (en) | 2010-05-11 | 2011-11-24 | Panasonic Corp | Method for grasping use of terminal and content and content use system |
US20110283189A1 (en) | 2010-05-12 | 2011-11-17 | Rovi Technologies Corporation | Systems and methods for adjusting media guide interaction modes |
US20110279368A1 (en) | 2010-05-12 | 2011-11-17 | Microsoft Corporation | Inferring user intent to engage a motion capture system |
US9634855B2 (en) | 2010-05-13 | 2017-04-25 | Alexander Poltorak | Electronic personal interactive device that determines topics of interest using a conversational agent |
US9628579B2 (en) | 2010-05-13 | 2017-04-18 | Futurewei Technologies, Inc. | System, apparatus for content delivery for internet traffic and methods thereof |
US9015139B2 (en) | 2010-05-14 | 2015-04-21 | Rovi Guides, Inc. | Systems and methods for performing a search based on a media content snapshot image |
US8745091B2 (en) | 2010-05-18 | 2014-06-03 | Integro, Inc. | Electronic document classification |
US8392186B2 (en) | 2010-05-18 | 2013-03-05 | K-Nfb Reading Technology, Inc. | Audio synchronization for document narration with user-selected playback |
US8694313B2 (en) | 2010-05-19 | 2014-04-08 | Google Inc. | Disambiguation of contact information using historical data |
US9552355B2 (en) | 2010-05-20 | 2017-01-24 | Xerox Corporation | Dynamic bi-phrases for statistical machine translation |
US8522283B2 (en) | 2010-05-20 | 2013-08-27 | Google Inc. | Television remote control data transfer |
US9236047B2 (en) | 2010-05-21 | 2016-01-12 | Microsoft Technology Licensing, Llc | Voice stream augmented note taking |
WO2011143827A1 (en) | 2010-05-21 | 2011-11-24 | Google Inc. | Input method editor |
US8606579B2 (en) | 2010-05-24 | 2013-12-10 | Microsoft Corporation | Voice print identification for identifying speakers |
US9569549B1 (en) | 2010-05-25 | 2017-02-14 | Amazon Technologies, Inc. | Location based recommendation and tagging of media content items |
JP2011250027A (en) | 2010-05-25 | 2011-12-08 | Panasonic Electric Works Co Ltd | Remote control device and information communication system |
US8468012B2 (en) | 2010-05-26 | 2013-06-18 | Google Inc. | Acoustic model adaptation using geographic information |
JP2013533996A (en) | 2010-05-31 | 2013-08-29 | バイドゥ オンライン ネットワーク テクノロジー(ペキン) カンパニー リミテッド | Method and apparatus used for mixed input of English and other characters |
US8639516B2 (en) | 2010-06-04 | 2014-01-28 | Apple Inc. | User-specific noise suppression for voice quality improvements |
US8458115B2 (en) | 2010-06-08 | 2013-06-04 | Microsoft Corporation | Mining topic-related aspects from user generated content |
ES2534047T3 (en) | 2010-06-08 | 2015-04-16 | Vodafone Holding Gmbh | Smart card with microphone |
US8954425B2 (en) | 2010-06-08 | 2015-02-10 | Microsoft Corporation | Snippet extraction and ranking |
US20110306426A1 (en) | 2010-06-10 | 2011-12-15 | Microsoft Corporation | Activity Participation Based On User Intent |
US20110307810A1 (en) | 2010-06-11 | 2011-12-15 | Isreal Hilerio | List integration |
US8234111B2 (en) | 2010-06-14 | 2012-07-31 | Google Inc. | Speech and noise models for speech recognition |
US20110314003A1 (en) | 2010-06-17 | 2011-12-22 | Microsoft Corporation | Template concatenation for capturing multiple concepts in a voice query |
US20120136572A1 (en) | 2010-06-17 | 2012-05-31 | Norton Kenneth S | Distance and Location-Aware Reminders in a Calendar System |
WO2011160140A1 (en) | 2010-06-18 | 2011-12-22 | Susan Bennett | System and method of semantic based searching |
US9443071B2 (en) | 2010-06-18 | 2016-09-13 | At&T Intellectual Property I, L.P. | Proximity based device security |
US8375320B2 (en) | 2010-06-22 | 2013-02-12 | Microsoft Corporation | Context-based task generation |
EP2400373A1 (en) | 2010-06-22 | 2011-12-28 | Vodafone Holding GmbH | Inputting symbols into an electronic device having a touch-screen |
US20110313803A1 (en) | 2010-06-22 | 2011-12-22 | Microsoft Corporation | Social Task Lists |
US9009592B2 (en) | 2010-06-22 | 2015-04-14 | Microsoft Technology Licensing, Llc | Population of lists and tasks from captured voice and audio content |
US8581844B2 (en) | 2010-06-23 | 2013-11-12 | Google Inc. | Switching between a first operational mode and a second operational mode using a natural motion gesture |
US8655901B1 (en) | 2010-06-23 | 2014-02-18 | Google Inc. | Translation-based query pattern mining |
US11068657B2 (en) | 2010-06-28 | 2021-07-20 | Skyscanner Limited | Natural language question answering system and method based on deep semantics |
US8250071B1 (en) | 2010-06-30 | 2012-08-21 | Amazon Technologies, Inc. | Disambiguation of term meaning |
JP5323770B2 (en) | 2010-06-30 | 2013-10-23 | 日本放送協会 | User instruction acquisition device, user instruction acquisition program, and television receiver |
CN101894547A (en) | 2010-06-30 | 2010-11-24 | 北京捷通华声语音技术有限公司 | Speech synthesis method and system |
US8411874B2 (en) | 2010-06-30 | 2013-04-02 | Google Inc. | Removing noise from audio |
US20120005602A1 (en) | 2010-07-02 | 2012-01-05 | Nokia Corporation | Methods and apparatuses for facilitating task switching |
EP2402867B1 (en) | 2010-07-02 | 2018-08-22 | Accenture Global Services Limited | A computer-implemented method, a computer program product and a computer system for image processing |
US8699821B2 (en) | 2010-07-05 | 2014-04-15 | Apple Inc. | Aligning images |
US20120010886A1 (en) | 2010-07-06 | 2012-01-12 | Javad Razavilar | Language Identification |
US8848882B2 (en) | 2010-07-07 | 2014-09-30 | Verizon Patent And Licensing Inc. | System for and method of measuring caller interactions during a call session |
US8249556B2 (en) | 2010-07-13 | 2012-08-21 | Google Inc. | Securing a mobile computing device |
US9104670B2 (en) | 2010-07-21 | 2015-08-11 | Apple Inc. | Customized search or acquisition of digital media assets |
US8260247B2 (en) | 2010-07-21 | 2012-09-04 | Research In Motion Limited | Portable electronic device and method of operation |
US9786159B2 (en) | 2010-07-23 | 2017-10-10 | Tivo Solutions Inc. | Multi-function remote control device |
CN103081514A (en) | 2010-07-23 | 2013-05-01 | 福纳克有限公司 | Hearing system and method for operating a hearing system |
US8861925B1 (en) | 2010-07-28 | 2014-10-14 | Intuit Inc. | Methods and systems for audio-visual synchronization |
JP5606205B2 (en) | 2010-07-28 | 2014-10-15 | 京セラ株式会社 | Mobile terminal device |
US8694537B2 (en) | 2010-07-29 | 2014-04-08 | Soundhound, Inc. | Systems and methods for enabling natural language processing |
KR101699720B1 (en) | 2010-08-03 | 2017-01-26 | 삼성전자주식회사 | Apparatus for voice command recognition and method thereof |
BRPI1004128A2 (en) | 2010-08-04 | 2012-04-10 | Magneti Marelli Sist S Automotivos Ind E Com Ltda | Setting Top Level Key Parameters for Biodiesel Logic Sensor |
US8775156B2 (en) | 2010-08-05 | 2014-07-08 | Google Inc. | Translating languages in response to device motion |
US9349368B1 (en) | 2010-08-05 | 2016-05-24 | Google Inc. | Generating an audio notification based on detection of a triggering event |
US8402533B2 (en) | 2010-08-06 | 2013-03-19 | Google Inc. | Input to locked computing device |
US8473289B2 (en) | 2010-08-06 | 2013-06-25 | Google Inc. | Disambiguating input based on context |
US8359020B2 (en) | 2010-08-06 | 2013-01-22 | Google Inc. | Automatically monitoring for voice input based on context |
US8731939B1 (en) | 2010-08-06 | 2014-05-20 | Google Inc. | Routing queries based on carrier phrase registration |
WO2012019637A1 (en) | 2010-08-09 | 2012-02-16 | Jadhav, Shubhangi Mahadeo | Visual music playlist creation and visual music track exploration |
CN101951553B (en) | 2010-08-17 | 2012-10-10 | 深圳市车音网科技有限公司 | Navigation method and system based on speech command |
EP2609749A4 (en) | 2010-08-27 | 2015-04-15 | Intel Corp | Peer to peer streaming of dvr buffered program data |
US8719006B2 (en) | 2010-08-27 | 2014-05-06 | Apple Inc. | Combined statistical and rule-based part-of-speech tagging for text-to-speech synthesis |
US8478519B2 (en) | 2010-08-30 | 2013-07-02 | Google Inc. | Providing results to parameterless search queries |
WO2012030838A1 (en) | 2010-08-30 | 2012-03-08 | Honda Motor Co., Ltd. | Belief tracking and action selection in spoken dialog systems |
US8225137B2 (en) | 2010-09-04 | 2012-07-17 | Cisco Technology, Inc. | System and method for providing media server redundancy in a network environment |
US9800721B2 (en) | 2010-09-07 | 2017-10-24 | Securus Technologies, Inc. | Multi-party conversation analyzer and logger |
EP2612261B1 (en) | 2010-09-08 | 2018-11-07 | Nuance Communications, Inc. | Internet search related methods and apparatus |
US8341142B2 (en) | 2010-09-08 | 2012-12-25 | Nuance Communications, Inc. | Methods and apparatus for searching the Internet |
US20120059655A1 (en) | 2010-09-08 | 2012-03-08 | Nuance Communications, Inc. | Methods and apparatus for providing input to a speech-enabled application program |
EP2614448A1 (en) | 2010-09-09 | 2013-07-17 | Sony Ericsson Mobile Communications AB | Annotating e-books/e-magazines with application results |
US9538229B2 (en) | 2010-09-15 | 2017-01-03 | Verizon Patent And Licensing Inc. | Media experience for touch screen devices |
US8560229B1 (en) | 2010-09-15 | 2013-10-15 | Google Inc. | Sensor based activity detection |
US20120068937A1 (en) | 2010-09-16 | 2012-03-22 | Sony Ericsson Mobile Communications Ab | Quick input language/virtual keyboard/ language dictionary change on a touch screen device |
US20120078635A1 (en) | 2010-09-24 | 2012-03-29 | Apple Inc. | Voice control system |
US8836638B2 (en) | 2010-09-25 | 2014-09-16 | Hewlett-Packard Development Company, L.P. | Silent speech based command to a computing device |
CN101937194B (en) | 2010-09-27 | 2012-12-19 | 鸿富锦精密工业(深圳)有限公司 | Intelligence control system with learning function and method thereof |
US8594997B2 (en) | 2010-09-27 | 2013-11-26 | Sap Ag | Context-aware conversational user interface |
KR20120031722A (en) | 2010-09-27 | 2012-04-04 | 삼성전자주식회사 | Apparatus and method for generating dynamic response |
US8719014B2 (en) | 2010-09-27 | 2014-05-06 | Apple Inc. | Electronic device with text error correction based on voice recognition data |
US10037319B2 (en) | 2010-09-29 | 2018-07-31 | Touchtype Limited | User input prediction |
CN102436456B (en) | 2010-09-29 | 2016-03-30 | 国际商业机器公司 | For the method and apparatus of classifying to named entity |
US8812321B2 (en) | 2010-09-30 | 2014-08-19 | At&T Intellectual Property I, L.P. | System and method for combining speech recognition outputs from a plurality of domain-specific speech recognizers via machine learning |
US8644519B2 (en) | 2010-09-30 | 2014-02-04 | Apple Inc. | Electronic devices with improved audio |
US20120084248A1 (en) | 2010-09-30 | 2012-04-05 | Microsoft Corporation | Providing suggestions based on user intent |
US8515736B1 (en) | 2010-09-30 | 2013-08-20 | Nuance Communications, Inc. | Training call routing applications by reusing semantically-labeled data collected for prior applications |
US20120084634A1 (en) | 2010-10-05 | 2012-04-05 | Sony Corporation | Method and apparatus for annotating text |
US8606293B2 (en) | 2010-10-05 | 2013-12-10 | Qualcomm Incorporated | Mobile device location estimation using environmental information |
US9679256B2 (en) | 2010-10-06 | 2017-06-13 | The Chancellor, Masters And Scholars Of The University Of Cambridge | Automated assessment of examination scripts |
US10900799B2 (en) | 2010-10-12 | 2021-01-26 | Toyota Motor Engineering & Manufacturing North America, Inc. | Systems and methods for determining a destination location from a communication |
DE112011103447T5 (en) | 2010-10-15 | 2013-08-22 | Intelligent Mechatronic Systems, Inc. | Man-machine interaction controlled by implicit assignment and polymorphism |
JP5572059B2 (en) | 2010-10-21 | 2014-08-13 | 京セラ株式会社 | Display device |
US20120108221A1 (en) | 2010-10-28 | 2012-05-03 | Microsoft Corporation | Augmenting communication sessions with applications |
US8335774B2 (en) | 2010-10-28 | 2012-12-18 | Google Inc. | Replacing a master media file |
WO2012055113A1 (en) | 2010-10-29 | 2012-05-03 | 安徽科大讯飞信息科技股份有限公司 | Method and system for endpoint automatic detection of audio record |
US20120110456A1 (en) | 2010-11-01 | 2012-05-03 | Microsoft Corporation | Integrated voice command modal user interface |
US8660531B2 (en) | 2010-11-03 | 2014-02-25 | Blackberry Limited | Access to locked functions |
US8831947B2 (en) | 2010-11-07 | 2014-09-09 | Nice Systems Ltd. | Method and apparatus for large vocabulary continuous speech recognition using a hybrid phoneme-word lattice |
US20120116770A1 (en) | 2010-11-08 | 2012-05-10 | Ming-Fu Chen | Speech data retrieving and presenting device |
EP2451141B1 (en) | 2010-11-09 | 2018-11-07 | BlackBerry Limited | Methods and apparatus to display mobile device contents |
US8352576B2 (en) | 2010-11-15 | 2013-01-08 | Google Inc. | Media file access |
US20120124172A1 (en) | 2010-11-15 | 2012-05-17 | Google Inc. | Providing Different Versions of a Media File |
MY177511A (en) | 2010-11-16 | 2020-09-17 | Shardul Suresh Shroff | System and method for providing virtual arbitration |
US20120124126A1 (en) | 2010-11-17 | 2012-05-17 | Microsoft Corporation | Contextual and task focused computing |
US10144440B2 (en) | 2010-11-17 | 2018-12-04 | General Electric Company | Methods and systems for data communications |
US9484018B2 (en) | 2010-11-23 | 2016-11-01 | At&T Intellectual Property I, L.P. | System and method for building and evaluating automatic speech recognition via an application programmer interface |
US8938216B2 (en) | 2010-11-24 | 2015-01-20 | Cisco Technology, Inc. | Geographical location information/signal quality-context based recording and playback of multimedia data from a conference session |
US9105008B2 (en) | 2010-11-29 | 2015-08-11 | Yahoo! Inc. | Detecting controversial events |
US8489625B2 (en) | 2010-11-29 | 2013-07-16 | Microsoft Corporation | Mobile query suggestions with time-location awareness |
US8862458B2 (en) | 2010-11-30 | 2014-10-14 | Sap Ag | Natural language interface |
WO2012074338A2 (en) | 2010-12-02 | 2012-06-07 | 에스케이텔레콤 주식회사 | Natural language and mathematical formula processing method and device therefor |
JP5652913B2 (en) | 2010-12-03 | 2015-01-14 | アイシン・エィ・ダブリュ株式会社 | In-vehicle terminal |
US9135241B2 (en) | 2010-12-08 | 2015-09-15 | At&T Intellectual Property I, L.P. | System and method for learning latent representations for natural language tasks |
US8312096B2 (en) | 2010-12-08 | 2012-11-13 | Google Inc. | Priority inbox notifications and synchronization for mobile messaging application |
US9244606B2 (en) | 2010-12-20 | 2016-01-26 | Apple Inc. | Device, method, and graphical user interface for navigation of concurrently open software applications |
US8666726B2 (en) | 2010-12-21 | 2014-03-04 | Nuance Communications, Inc. | Sample clustering to reduce manual transcriptions in speech recognition system |
US20120158422A1 (en) | 2010-12-21 | 2012-06-21 | General Electric Company | Methods and systems for scheduling appointments in healthcare systems |
US20120158293A1 (en) | 2010-12-21 | 2012-06-21 | General Electric Company | Methods and systems for dynamically providing users with appointment reminders |
US8532377B2 (en) | 2010-12-22 | 2013-09-10 | Xerox Corporation | Image ranking based on abstract concepts |
US20130035086A1 (en) | 2010-12-22 | 2013-02-07 | Logitech Europe S.A. | Remote control system for providing content suggestions |
US8838449B2 (en) | 2010-12-23 | 2014-09-16 | Microsoft Corporation | Word-dependent language model |
US20120166959A1 (en) | 2010-12-23 | 2012-06-28 | Microsoft Corporation | Surfacing content including content accessed from jump list tasks and items |
JP2012142744A (en) | 2010-12-28 | 2012-07-26 | Sanyo Electric Co Ltd | Communication device |
TWI413105B (en) | 2010-12-30 | 2013-10-21 | Ind Tech Res Inst | Multi-lingual text-to-speech synthesis system and method |
US8626681B1 (en) | 2011-01-04 | 2014-01-07 | Google Inc. | Training a probabilistic spelling checker from structured data |
KR101828273B1 (en) | 2011-01-04 | 2018-02-14 | 삼성전자주식회사 | Apparatus and method for voice command recognition based on combination of dialog models |
US8589950B2 (en) | 2011-01-05 | 2013-11-19 | Blackberry Limited | Processing user input events in a web browser |
JP5809290B2 (en) | 2011-01-05 | 2015-11-10 | グーグル・インコーポレーテッド | Method and system for facilitating text entry |
US8898065B2 (en) | 2011-01-07 | 2014-11-25 | Nuance Communications, Inc. | Configurable speech recognition system using multiple recognizers |
CA2821565C (en) | 2011-01-07 | 2017-04-18 | Research In Motion Limited | System and method for controlling mobile communication devices |
US9183843B2 (en) | 2011-01-07 | 2015-11-10 | Nuance Communications, Inc. | Configurable speech recognition system using multiple recognizers |
JP5712618B2 (en) | 2011-01-07 | 2015-05-07 | サクサ株式会社 | Telephone system |
US8689116B2 (en) | 2011-01-14 | 2014-04-01 | Apple Inc. | Email user interface |
US8863256B1 (en) | 2011-01-14 | 2014-10-14 | Cisco Technology, Inc. | System and method for enabling secure transactions using flexible identity management in a vehicular environment |
US8666895B2 (en) | 2011-01-31 | 2014-03-04 | Bank Of America Corporation | Single action mobile transaction device |
US8943054B2 (en) | 2011-01-31 | 2015-01-27 | Social Resolve, Llc | Social media content management system and method |
AU2012212517A1 (en) | 2011-02-04 | 2013-08-22 | Google Inc. | Posting to social networks by voice |
US8862612B2 (en) | 2011-02-11 | 2014-10-14 | Sony Corporation | Direct search launch on a second display |
US8620709B2 (en) | 2011-02-11 | 2013-12-31 | Avaya, Inc | Mobile activity manager |
US10631246B2 (en) | 2011-02-14 | 2020-04-21 | Microsoft Technology Licensing, Llc | Task switching on mobile devices |
US9916420B2 (en) | 2011-02-18 | 2018-03-13 | Nuance Communications, Inc. | Physician and clinical documentation specialist workflow integration |
US8694335B2 (en) | 2011-02-18 | 2014-04-08 | Nuance Communications, Inc. | Methods and apparatus for applying user corrections to medical fact extraction |
KR101178310B1 (en) | 2011-02-24 | 2012-08-29 | 포항공과대학교 산학협력단 | Method of managing communication and system for the same |
US10145960B2 (en) | 2011-02-24 | 2018-12-04 | Ford Global Technologies, Llc | System and method for cell phone restriction |
CN102651217A (en) | 2011-02-25 | 2012-08-29 | 株式会社东芝 | Method and equipment for voice synthesis and method for training acoustic model used in voice synthesis |
US8688453B1 (en) | 2011-02-28 | 2014-04-01 | Nuance Communications, Inc. | Intent mining via analysis of utterances |
US20120221552A1 (en) | 2011-02-28 | 2012-08-30 | Nokia Corporation | Method and apparatus for providing an active search user interface element |
US9632677B2 (en) | 2011-03-02 | 2017-04-25 | The Boeing Company | System and method for navigating a 3-D environment using a multi-input interface |
US8972275B2 (en) | 2011-03-03 | 2015-03-03 | Brightedge Technologies, Inc. | Optimization of social media engagement |
EP2498250B1 (en) | 2011-03-07 | 2021-05-05 | Accenture Global Services Limited | Client and server system for natural language-based control of a digital network of devices |
US9081760B2 (en) | 2011-03-08 | 2015-07-14 | At&T Intellectual Property I, L.P. | System and method for building diverse language models |
US20120233266A1 (en) | 2011-03-11 | 2012-09-13 | Microsoft Corporation | Peer-to-peer group with renegotiation of group owner |
CN202092650U (en) | 2011-03-14 | 2011-12-28 | 深圳市车乐数码科技有限公司 | Vehicle-mounted multimedia device with keys and voice navigation function |
US8849931B2 (en) | 2011-03-15 | 2014-09-30 | Idt Messaging, Llc | Linking context-based information to text messages |
US8606090B2 (en) | 2011-03-17 | 2013-12-10 | Sony Corporation | Sport program chaptering |
US9262612B2 (en) | 2011-03-21 | 2016-02-16 | Apple Inc. | Device access using voice authentication |
US8862255B2 (en) | 2011-03-23 | 2014-10-14 | Audible, Inc. | Managing playback of synchronized content |
US20120246064A1 (en) | 2011-03-23 | 2012-09-27 | Ebay, Inc. | Customer refunds using payment service providers |
US8766793B2 (en) | 2011-03-25 | 2014-07-01 | Microsoft Corporation | Contextually-appropriate task reminders |
US9202465B2 (en) | 2011-03-25 | 2015-12-01 | General Motors Llc | Speech recognition dependent on text message content |
US9171546B1 (en) | 2011-03-29 | 2015-10-27 | Google Inc. | Performing functions based on commands in context of telephonic communication |
CN202035047U (en) | 2011-03-29 | 2011-11-09 | 张磊 | Mobile terminal capable of extracting address information for navigation |
US9154555B2 (en) | 2011-03-30 | 2015-10-06 | Paypal, Inc. | Device specific remote disabling of applications |
US9842168B2 (en) | 2011-03-31 | 2017-12-12 | Microsoft Technology Licensing, Llc | Task driven user intents |
EP2691870A4 (en) | 2011-03-31 | 2015-05-20 | Microsoft Technology Licensing Llc | Task driven user intents |
US9280535B2 (en) | 2011-03-31 | 2016-03-08 | Infosys Limited | Natural language querying with cascaded conditional random fields |
US9337999B2 (en) | 2011-04-01 | 2016-05-10 | Intel Corporation | Application usage continuum across platforms |
US9098488B2 (en) | 2011-04-03 | 2015-08-04 | Microsoft Technology Licensing, Llc | Translation of multilingual embedded phrases |
US20120252367A1 (en) | 2011-04-04 | 2012-10-04 | Meditalk Devices, Llc | Auditory Speech Module For Medical Devices |
CN103562863A (en) | 2011-04-04 | 2014-02-05 | 惠普发展公司,有限责任合伙企业 | Creating a correlation rule defining a relationship between event types |
US8914275B2 (en) | 2011-04-06 | 2014-12-16 | Microsoft Corporation | Text prediction |
CN102137193A (en) | 2011-04-13 | 2011-07-27 | 深圳凯虹移动通信有限公司 | Mobile communication terminal and communication control method thereof |
US9292877B2 (en) | 2011-04-13 | 2016-03-22 | Longsand Limited | Methods and systems for generating concept-based hash tags |
US9366749B2 (en) | 2011-04-15 | 2016-06-14 | Qualcomm Incorporated | Device position estimates from motion and ambient light classifiers |
US9493130B2 (en) | 2011-04-22 | 2016-11-15 | Angel A. Penilla | Methods and systems for communicating content to connected vehicle users based detected tone/mood in voice input |
JP2014520297A (en) | 2011-04-25 | 2014-08-21 | ベベオ,インク. | System and method for advanced personal timetable assistant |
US9444692B2 (en) | 2011-04-26 | 2016-09-13 | Openet Telecom Ltd. | Systems, devices and methods of crowd-sourcing across multiple domains |
US9110556B2 (en) | 2011-04-28 | 2015-08-18 | Nokia Technologies Oy | Method and apparatus for increasing the functionality of an electronic device in a locked state |
CN102981746A (en) | 2011-05-03 | 2013-03-20 | 宏达国际电子股份有限公司 | Handheld electronic device and method for calibrating input of webpage address |
CN102870065B (en) | 2011-05-04 | 2016-01-20 | 黑莓有限公司 | For adjusting the method presented of the graph data that graphic user interface shows |
US8171137B1 (en) | 2011-05-09 | 2012-05-01 | Google Inc. | Transferring application state across devices |
US8150385B1 (en) | 2011-05-09 | 2012-04-03 | Loment, Inc. | Automated reply messages among end user communication devices |
EP2707872A2 (en) | 2011-05-12 | 2014-03-19 | Johnson Controls Technology Company | Adaptive voice recognition systems and methods |
US9064006B2 (en) | 2012-08-23 | 2015-06-23 | Microsoft Technology Licensing, Llc | Translating natural language utterances to keyword search queries |
KR101233561B1 (en) | 2011-05-12 | 2013-02-14 | 엔에이치엔(주) | Speech recognition system and method based on word-level candidate generation |
WO2012158469A2 (en) | 2011-05-13 | 2012-11-22 | Plimpton David | Calendar-based search engine |
US20120290291A1 (en) | 2011-05-13 | 2012-11-15 | Gabriel Lee Gilbert Shelley | Input processing for character matching and predicted word matching |
US8793624B2 (en) | 2011-05-18 | 2014-07-29 | Google Inc. | Control of a device using gestures |
US8972240B2 (en) | 2011-05-19 | 2015-03-03 | Microsoft Corporation | User-modifiable word lattice display for editing documents and search queries |
US8914290B2 (en) | 2011-05-20 | 2014-12-16 | Vocollect, Inc. | Systems and methods for dynamically improving user intelligibility of synthesized speech in a work environment |
US20120304124A1 (en) | 2011-05-23 | 2012-11-29 | Microsoft Corporation | Context aware input engine |
US10522133B2 (en) | 2011-05-23 | 2019-12-31 | Nuance Communications, Inc. | Methods and apparatus for correcting recognition errors |
US8731936B2 (en) | 2011-05-26 | 2014-05-20 | Microsoft Corporation | Energy-efficient unobtrusive identification of a speaker |
US9164983B2 (en) | 2011-05-27 | 2015-10-20 | Robert Bosch Gmbh | Broad-coverage normalization system for social media language |
US9268857B2 (en) | 2011-06-03 | 2016-02-23 | Facebook, Inc. | Suggesting search results to users before receiving any search query from the users |
US10672399B2 (en) | 2011-06-03 | 2020-06-02 | Apple Inc. | Switching between text data and audio data based on a mapping |
US10057736B2 (en) | 2011-06-03 | 2018-08-21 | Apple Inc. | Active transport based notifications |
JP5463385B2 (en) | 2011-06-03 | 2014-04-09 | アップル インコーポレイテッド | Automatic creation of mapping between text data and audio data |
US8781841B1 (en) | 2011-06-07 | 2014-07-15 | Cisco Technology, Inc. | Name recognition of virtual meeting participants |
US20120317498A1 (en) | 2011-06-07 | 2012-12-13 | Research In Motion Limited | Electronic communication device and method for displaying icons |
WO2012170817A1 (en) | 2011-06-10 | 2012-12-13 | Google Inc. | Augmenting statistical machine translation with linguistic knowledge |
US20120316875A1 (en) | 2011-06-10 | 2012-12-13 | Red Shift Company, Llc | Hosted speech handling |
US8732319B2 (en) | 2011-06-10 | 2014-05-20 | Qualcomm Incorporated | Context awareness proximity-based establishment of wireless communication connection |
US20130158977A1 (en) | 2011-06-14 | 2013-06-20 | Andrew Senior | System and Method for Evaluating Speech Exposure |
US20120324391A1 (en) | 2011-06-16 | 2012-12-20 | Microsoft Corporation | Predictive word completion |
US20120321112A1 (en) | 2011-06-16 | 2012-12-20 | Apple Inc. | Selecting a digital stream based on an audio sample |
CN102237088B (en) | 2011-06-17 | 2013-10-23 | 盛乐信息技术(上海)有限公司 | Device and method for acquiring speech recognition multi-information text |
US20120329529A1 (en) | 2011-06-21 | 2012-12-27 | GreatCall, Inc. | Gesture activate help process and system |
CN104011712B (en) | 2011-06-24 | 2018-04-24 | 谷歌有限责任公司 | To being evaluated across the query translation of language inquiry suggestion |
US10984387B2 (en) | 2011-06-28 | 2021-04-20 | Microsoft Technology Licensing, Llc | Automatic task extraction and calendar entry |
US20130007240A1 (en) | 2011-06-30 | 2013-01-03 | At&T Intellectual Property I, L.P. | Systems and methods to provide availability notifications for denied content requests |
WO2012103726A1 (en) | 2011-06-30 | 2012-08-09 | 华为技术有限公司 | Method, apparatus, and system for transmitting media data based on over the top (ott) |
US20130006633A1 (en) | 2011-07-01 | 2013-01-03 | Qualcomm Incorporated | Learning speech models for mobile device users |
US9367824B2 (en) | 2011-07-05 | 2016-06-14 | Sap Se | Provisioning and performing action items |
DE102011078642A1 (en) | 2011-07-05 | 2013-01-10 | Robert Bosch Gmbh | Method for checking an m out of n code |
US20140100847A1 (en) | 2011-07-05 | 2014-04-10 | Mitsubishi Electric Corporation | Voice recognition device and navigation device |
US8209183B1 (en) | 2011-07-07 | 2012-06-26 | Google Inc. | Systems and methods for correction of text from different input types, sources, and contexts |
US8682670B2 (en) | 2011-07-07 | 2014-03-25 | International Business Machines Corporation | Statistical enhancement of speech output from a statistical text-to-speech synthesis system |
US20130010575A1 (en) | 2011-07-07 | 2013-01-10 | International Business Machines Corporation | Systems and methods of managing electronic calendar applications |
US8665212B2 (en) | 2011-07-08 | 2014-03-04 | Blackberry Limited | Systems and methods for locking an electronic device |
US20130018659A1 (en) | 2011-07-12 | 2013-01-17 | Google Inc. | Systems and Methods for Speech Command Processing |
CA2747153A1 (en) | 2011-07-19 | 2013-01-19 | Suleman Kaheer | Natural language processing dialog system for obtaining goods, services or information |
US20130024576A1 (en) | 2011-07-22 | 2013-01-24 | Microsoft Corporation | Proximity-Based Detection |
US8781810B2 (en) | 2011-07-25 | 2014-07-15 | Xerox Corporation | System and method for productive generation of compound words in statistical machine translation |
US20130031476A1 (en) | 2011-07-25 | 2013-01-31 | Coin Emmett | Voice activated virtual assistant |
US8732028B2 (en) | 2011-07-26 | 2014-05-20 | Expose Retail Strategies Inc. | Scheduling of order processing for remotely ordered goods |
US9009041B2 (en) | 2011-07-26 | 2015-04-14 | Nuance Communications, Inc. | Systems and methods for improving the accuracy of a transcription using auxiliary data such as personal data |
US9031842B2 (en) | 2011-07-28 | 2015-05-12 | Blackberry Limited | Methods and devices for facilitating communications |
EP2551784A1 (en) | 2011-07-28 | 2013-01-30 | Roche Diagnostics GmbH | Method of controlling the display of a dataset |
US9292112B2 (en) | 2011-07-28 | 2016-03-22 | Hewlett-Packard Development Company, L.P. | Multimodal interface |
US20130030913A1 (en) | 2011-07-29 | 2013-01-31 | Guangyu Zhu | Deriving Ads Ranking of Local Advertisers based on Distance and Aggregate User Activities |
CN102905499B (en) | 2011-07-29 | 2015-12-09 | 纬创资通股份有限公司 | Vertical card module and electronic installation |
US20130031177A1 (en) | 2011-07-29 | 2013-01-31 | Myxer, Inc. | Systems and methods for dynamic media selection |
US20130030789A1 (en) | 2011-07-29 | 2013-01-31 | Reginald Dalce | Universal Language Translator |
US20130035117A1 (en) | 2011-08-04 | 2013-02-07 | GM Global Technology Operations LLC | System and method for restricting driver mobile device feature usage while vehicle is in motion |
WO2013022218A2 (en) | 2011-08-05 | 2013-02-14 | Samsung Electronics Co., Ltd. | Electronic apparatus and method for providing user interface thereof |
WO2013022222A2 (en) | 2011-08-05 | 2013-02-14 | Samsung Electronics Co., Ltd. | Method for controlling electronic apparatus based on motion recognition, and electronic apparatus applying the same |
EP3413575A1 (en) | 2011-08-05 | 2018-12-12 | Samsung Electronics Co., Ltd. | Method for controlling electronic apparatus based on voice recognition and electronic apparatus applying the same |
US9417754B2 (en) | 2011-08-05 | 2016-08-16 | P4tents1, LLC | User interface system, method, and computer program product |
US8595015B2 (en) | 2011-08-08 | 2013-11-26 | Verizon New Jersey Inc. | Audio communication assessment |
CN102929710B (en) | 2011-08-09 | 2017-10-27 | 中兴通讯股份有限公司 | A kind of method and mobile terminal for calling application module |
US8706472B2 (en) | 2011-08-11 | 2014-04-22 | Apple Inc. | Method for disambiguating multiple readings in language conversion |
WO2013022135A1 (en) | 2011-08-11 | 2013-02-14 | Lg Electronics Inc. | Electronic device and method of controlling the same |
US8589160B2 (en) | 2011-08-19 | 2013-11-19 | Dolbey & Company, Inc. | Systems and methods for providing an electronic dictation interface |
US20130055099A1 (en) | 2011-08-22 | 2013-02-28 | Rose Yao | Unified Messaging System with Integration of Call Log Data |
US8943071B2 (en) | 2011-08-23 | 2015-01-27 | At&T Intellectual Property I, L.P. | Automatic sort and propagation associated with electronic documents |
US9195768B2 (en) | 2011-08-26 | 2015-11-24 | Amazon Technologies, Inc. | Remote browsing session management |
US20130054706A1 (en) | 2011-08-29 | 2013-02-28 | Mary Graham | Modulation of Visual Notification Parameters Based on Message Activity and Notification Value |
US8994660B2 (en) | 2011-08-29 | 2015-03-31 | Apple Inc. | Text correction processing |
US20130055147A1 (en) | 2011-08-29 | 2013-02-28 | Salesforce.Com, Inc. | Configuration, generation, and presentation of custom graphical user interface components for a virtual cloud-based application |
US20130054631A1 (en) | 2011-08-30 | 2013-02-28 | Microsoft Corporation | Adding social network data to search suggestions |
US8819012B2 (en) | 2011-08-30 | 2014-08-26 | International Business Machines Corporation | Accessing anchors in voice site content |
US8554729B2 (en) | 2011-08-31 | 2013-10-08 | Google Inc. | System and method for synchronization of actions in the background of an application |
US8914288B2 (en) | 2011-09-01 | 2014-12-16 | At&T Intellectual Property I, L.P. | System and method for advanced turn-taking for interactive spoken dialog systems |
WO2013033910A1 (en) | 2011-09-09 | 2013-03-14 | Google Inc. | User interface for translation webpage |
US9596084B2 (en) | 2011-09-09 | 2017-03-14 | Facebook, Inc. | Initializing camera subsystem for face detection based on sensor inputs |
US20130066832A1 (en) | 2011-09-12 | 2013-03-14 | Microsoft Corporation | Application state synchronization |
US20130073346A1 (en) | 2011-09-16 | 2013-03-21 | David Chun | Identifying companies most closely related to a given company |
US20130073286A1 (en) | 2011-09-20 | 2013-03-21 | Apple Inc. | Consolidating Speech Recognition Results |
CN103947219A (en) | 2011-09-21 | 2014-07-23 | 瑞典爱立信有限公司 | Methods, devices and computer programs for transmitting or for receiving and playing media streams |
US8699963B2 (en) | 2011-09-22 | 2014-04-15 | Blackberry Limited | Mobile communication device with receiver speaker |
US9129606B2 (en) | 2011-09-23 | 2015-09-08 | Microsoft Technology Licensing, Llc | User query history expansion for improving language model adaptation |
US8798995B1 (en) | 2011-09-23 | 2014-08-05 | Amazon Technologies, Inc. | Key word determinations from voice data |
US8812301B2 (en) | 2011-09-26 | 2014-08-19 | Xerox Corporation | Linguistically-adapted structural query annotation |
US20130080251A1 (en) | 2011-09-26 | 2013-03-28 | Accenture Global Services Limited | Product registration and tracking system |
KR20130032966A (en) | 2011-09-26 | 2013-04-03 | 엘지전자 주식회사 | Method and device for user interface |
US8768707B2 (en) | 2011-09-27 | 2014-07-01 | Sensory Incorporated | Background speech recognition assistant using speaker verification |
US8996381B2 (en) | 2011-09-27 | 2015-03-31 | Sensory, Incorporated | Background speech recognition assistant |
US8762156B2 (en) | 2011-09-28 | 2014-06-24 | Apple Inc. | Speech recognition repair using contextual information |
US8452597B2 (en) | 2011-09-30 | 2013-05-28 | Google Inc. | Systems and methods for continual speech recognition and detection in mobile computing devices |
US8468022B2 (en) | 2011-09-30 | 2013-06-18 | Google Inc. | Voice control for asynchronous notifications |
AU2015203483A1 (en) | 2011-09-30 | 2015-07-16 | Apple Inc. | Using context information to facilitate processing of commands in a virtual assistant |
US8452602B1 (en) | 2011-09-30 | 2013-05-28 | Google Inc. | Structuring verbal commands to allow concatenation in a voice interface in a mobile device |
DE102012019178A1 (en) | 2011-09-30 | 2013-04-04 | Apple Inc. | Use of context information to facilitate the handling of commands in a virtual assistant |
AU2012316484A1 (en) | 2011-09-30 | 2014-04-17 | Apple Inc. | Automatically adapting user interfaces for hands-free interaction |
US8340975B1 (en) | 2011-10-04 | 2012-12-25 | Theodore Alfred Rosenberger | Interactive speech recognition device and system for hands-free building control |
US8386926B1 (en) | 2011-10-06 | 2013-02-26 | Google Inc. | Network-based custom dictionary, auto-correction and text entry preferences |
US9521175B2 (en) | 2011-10-07 | 2016-12-13 | Henk B. Rogers | Media tagging |
US9640175B2 (en) | 2011-10-07 | 2017-05-02 | Microsoft Technology Licensing, Llc | Pronunciation learning from user correction |
US8738363B2 (en) | 2011-10-13 | 2014-05-27 | Xerox Corporation | System and method for suggestion mining |
US9021565B2 (en) | 2011-10-13 | 2015-04-28 | At&T Intellectual Property I, L.P. | Authentication techniques utilizing a computing device |
US20130097566A1 (en) | 2011-10-17 | 2013-04-18 | Carl Fredrik Alexander BERGLUND | System and method for displaying items on electronic devices |
KR101873741B1 (en) | 2011-10-26 | 2018-07-03 | 엘지전자 주식회사 | Mobile terminal and method for controlling the same |
US8738376B1 (en) | 2011-10-28 | 2014-05-27 | Nuance Communications, Inc. | Sparse maximum a posteriori (MAP) adaptation |
US20130111330A1 (en) | 2011-11-01 | 2013-05-02 | Research In Motion Limited | Accelerated compositing of fixed position elements on an electronic device |
US9223948B2 (en) | 2011-11-01 | 2015-12-29 | Blackberry Limited | Combined passcode and activity launch modifier |
US9471666B2 (en) * | 2011-11-02 | 2016-10-18 | Salesforce.Com, Inc. | System and method for supporting natural language queries and requests against a user's personal data cloud |
US9736089B2 (en) | 2011-11-02 | 2017-08-15 | Blackberry Limited | System and method for enabling voice and video communications using a messaging application |
US20130110943A1 (en) | 2011-11-02 | 2013-05-02 | Apple Inc. | Notification and reminder generation, distribution, and storage system |
US8996350B1 (en) | 2011-11-02 | 2015-03-31 | Dub Software Group, Inc. | System and method for automatic document management |
CN103093334A (en) | 2011-11-04 | 2013-05-08 | 周超然 | Method of activity notice text recognition and transforming automatically into calendar term |
JP5681611B2 (en) | 2011-11-09 | 2015-03-11 | 株式会社日立製作所 | Navigation system, navigation apparatus, method, and server |
US9711137B2 (en) | 2011-11-10 | 2017-07-18 | At&T Intellectual Property I, Lp | Network-based background expert |
US8863202B2 (en) | 2011-11-11 | 2014-10-14 | Sony Corporation | System and method for voice driven cross service search using second display |
US8972263B2 (en) | 2011-11-18 | 2015-03-03 | Soundhound, Inc. | System and method for performing dual mode speech recognition |
CN103135916A (en) | 2011-11-30 | 2013-06-05 | 英特尔公司 | Intelligent graphical interface in handheld wireless device |
KR101830656B1 (en) | 2011-12-02 | 2018-02-21 | 엘지전자 주식회사 | Mobile terminal and control method for the same |
US9214157B2 (en) | 2011-12-06 | 2015-12-15 | At&T Intellectual Property I, L.P. | System and method for machine-mediated human-human conversation |
KR101193668B1 (en) | 2011-12-06 | 2012-12-14 | 위준성 | Foreign language acquisition and learning service providing method based on context-aware using smart device |
US9323746B2 (en) | 2011-12-06 | 2016-04-26 | At&T Intellectual Property I, L.P. | System and method for collaborative language translation |
US9082402B2 (en) | 2011-12-08 | 2015-07-14 | Sri International | Generic virtual personal assistant platform |
US9646313B2 (en) | 2011-12-13 | 2017-05-09 | Microsoft Technology Licensing, Llc | Gesture-based tagging to view related content |
US20130159847A1 (en) | 2011-12-14 | 2013-06-20 | International Business Machines Corporation | Dynamic Personal Dictionaries for Enhanced Collaboration |
WO2013090839A1 (en) | 2011-12-14 | 2013-06-20 | Realnetworks, Inc. | Customizable media auto-reply systems and methods |
CN202453859U (en) | 2011-12-20 | 2012-09-26 | 安徽科大讯飞信息科技股份有限公司 | Voice interaction device for home appliance |
US8622836B2 (en) | 2011-12-22 | 2014-01-07 | Igt | Use of wireless signal strength to determine connection |
JP2013134430A (en) | 2011-12-27 | 2013-07-08 | Toyota Motor Corp | Device, method, and program for processing command |
US8996729B2 (en) | 2012-04-12 | 2015-03-31 | Nokia Corporation | Method and apparatus for synchronizing tasks performed by multiple devices |
US8886630B2 (en) * | 2011-12-29 | 2014-11-11 | Mcafee, Inc. | Collaborative searching |
US9094534B2 (en) | 2011-12-29 | 2015-07-28 | Apple Inc. | Device, method, and graphical user interface for configuring and implementing restricted interactions with a user interface |
US9836177B2 (en) | 2011-12-30 | 2017-12-05 | Next IT Innovation Labs, LLC | Providing variable responses in a virtual-assistant environment |
JP5790509B2 (en) | 2012-01-05 | 2015-10-07 | 富士通株式会社 | Image reproduction apparatus, image reproduction program, and image reproduction method |
JP5887937B2 (en) | 2012-01-06 | 2016-03-16 | 株式会社リコー | Output control system, output control method, output control device, and output control program |
JP5547216B2 (en) | 2012-01-06 | 2014-07-09 | 株式会社東芝 | Electronic device and display control method |
US9547832B2 (en) | 2012-01-10 | 2017-01-17 | Oracle International Corporation | Identifying individual intentions and determining responses to individual intentions |
US8825020B2 (en) | 2012-01-12 | 2014-09-02 | Sensory, Incorporated | Information access and device control using mobile phones and audio in the home environment |
CN103209369A (en) | 2012-01-16 | 2013-07-17 | 晨星软件研发(深圳)有限公司 | Voice-controlled system of electronic device and related control method |
US8812302B2 (en) | 2012-01-17 | 2014-08-19 | Google Inc. | Techniques for inserting diacritical marks to text input via a user device |
US9134810B2 (en) | 2012-01-19 | 2015-09-15 | Blackberry Limited | Next letter prediction for virtual keyboard |
US9099098B2 (en) | 2012-01-20 | 2015-08-04 | Qualcomm Incorporated | Voice activity detection in presence of background noise |
US20130204813A1 (en) | 2012-01-20 | 2013-08-08 | Fluential, Llc | Self-learning, context aware virtual assistants, systems and methods |
EP2807455A4 (en) | 2012-01-26 | 2015-08-12 | Telecomm Systems Inc | Natural navigational guidance |
JP5682578B2 (en) | 2012-01-27 | 2015-03-11 | 日本電気株式会社 | Speech recognition result correction support system, speech recognition result correction support method, and speech recognition result correction support program |
US8745760B2 (en) | 2012-01-30 | 2014-06-03 | Cisco Technology, Inc. | Malware classification for unknown executable files |
US8626748B2 (en) | 2012-02-03 | 2014-01-07 | International Business Machines Corporation | Combined word tree text visualization system |
US9253135B2 (en) | 2012-02-07 | 2016-02-02 | Google Inc. | Notification management |
CN102629246B (en) | 2012-02-10 | 2017-06-27 | 百纳(武汉)信息技术有限公司 | Recognize the server and browser voice command identification method of browser voice command |
US8995960B2 (en) | 2012-02-10 | 2015-03-31 | Dedo Interactive, Inc. | Mobile device authentication |
US10209954B2 (en) | 2012-02-14 | 2019-02-19 | Microsoft Technology Licensing, Llc | Equal access to speech and touch input |
JP2013167806A (en) | 2012-02-16 | 2013-08-29 | Toshiba Corp | Information notification supporting device, information notification supporting method, and program |
US8832092B2 (en) | 2012-02-17 | 2014-09-09 | Bottlenose, Inc. | Natural language processing optimized for micro content |
US9064497B2 (en) | 2012-02-22 | 2015-06-23 | Htc Corporation | Method and apparatus for audio intelligibility enhancement and computing apparatus |
WO2013123572A1 (en) | 2012-02-24 | 2013-08-29 | Research In Motion Limited | Touchscreen keyboard providing word predictions in partitions of the touchscreen keyboard in proximate association with candidate letters |
KR101889836B1 (en) | 2012-02-24 | 2018-08-20 | 삼성전자주식회사 | Method and apparatus for cotrolling lock/unlock state of terminal through voice recognition |
US9042867B2 (en) | 2012-02-24 | 2015-05-26 | Agnitio S.L. | System and method for speaker recognition on mobile devices |
US8543398B1 (en) | 2012-02-29 | 2013-09-24 | Google Inc. | Training an automatic speech recognition system using compressed word frequencies |
US10984337B2 (en) | 2012-02-29 | 2021-04-20 | Microsoft Technology Licensing, Llc | Context-based search query formation |
US10134385B2 (en) | 2012-03-02 | 2018-11-20 | Apple Inc. | Systems and methods for name pronunciation |
US20130235987A1 (en) | 2012-03-06 | 2013-09-12 | Jose Arroniz-Escobar | Automatic machine to machine distribution of subscriber contact information |
US20130238326A1 (en) | 2012-03-08 | 2013-09-12 | Lg Electronics Inc. | Apparatus and method for multiple device voice control |
US9639174B2 (en) | 2012-03-09 | 2017-05-02 | Paypal, Inc. | Mobile device display content based on shaking the device |
US20150006157A1 (en) | 2012-03-14 | 2015-01-01 | Nec Corporation | Term synonym acquisition method and term synonym acquisition apparatus |
US9576593B2 (en) | 2012-03-15 | 2017-02-21 | Regents Of The University Of Minnesota | Automated verbal fluency assessment |
EP2639792A1 (en) | 2012-03-16 | 2013-09-18 | France Télécom | Voice control of applications by associating user input with action-context idendifier pairs |
US9223497B2 (en) | 2012-03-16 | 2015-12-29 | Blackberry Limited | In-context word prediction and word correction |
JP5870790B2 (en) | 2012-03-19 | 2016-03-01 | 富士通株式会社 | Sentence proofreading apparatus and proofreading method |
JP2013200423A (en) | 2012-03-23 | 2013-10-03 | Toshiba Corp | Voice interaction support device, method and program |
US9135955B2 (en) | 2012-03-26 | 2015-09-15 | Max Abecassis | Playing a video presentation with playback functions |
JP5965175B2 (en) | 2012-03-27 | 2016-08-03 | ヤフー株式会社 | Response generation apparatus, response generation method, and response generation program |
US8681950B2 (en) | 2012-03-28 | 2014-03-25 | Interactive Intelligence, Inc. | System and method for fingerprinting datasets |
US10237696B2 (en) | 2012-03-29 | 2019-03-19 | Intel Corporation | Location-based assistance for personal planning |
US8346563B1 (en) | 2012-04-10 | 2013-01-01 | Artificial Solutions Ltd. | System and methods for delivering advanced natural language interaction applications |
US8892419B2 (en) | 2012-04-10 | 2014-11-18 | Artificial Solutions Iberia SL | System and methods for semiautomatic generation and tuning of natural language interaction applications |
US20130275117A1 (en) | 2012-04-11 | 2013-10-17 | Morgan H. Winer | Generalized Phonetic Transliteration Engine |
US9685160B2 (en) | 2012-04-16 | 2017-06-20 | Htc Corporation | Method for offering suggestion during conversation, electronic device using the same, and non-transitory storage medium |
US20130282709A1 (en) | 2012-04-18 | 2013-10-24 | Yahoo! Inc. | Method and system for query suggestion |
US9223537B2 (en) | 2012-04-18 | 2015-12-29 | Next It Corporation | Conversation user interface |
WO2013155619A1 (en) | 2012-04-20 | 2013-10-24 | Sam Pasupalak | Conversational agent |
US9117449B2 (en) | 2012-04-26 | 2015-08-25 | Nuance Communications, Inc. | Embedded system for construction of small footprint speech recognition with user-definable constraints |
TWI511537B (en) | 2012-04-27 | 2015-12-01 | Wistron Corp | Smart tv system, smart tv, mobile device and input operation method thereof |
CN102682771B (en) | 2012-04-27 | 2013-11-20 | 厦门思德电子科技有限公司 | Multi-speech control method suitable for cloud platform |
US20130289991A1 (en) | 2012-04-30 | 2013-10-31 | International Business Machines Corporation | Application of Voice Tags in a Social Media Context |
US20130285916A1 (en) | 2012-04-30 | 2013-10-31 | Research In Motion Limited | Touchscreen keyboard providing word predictions at locations in association with candidate letters |
KR101946364B1 (en) | 2012-05-01 | 2019-02-11 | 엘지전자 주식회사 | Mobile device for having at least one microphone sensor and method for controlling the same |
US9058332B1 (en) * | 2012-05-04 | 2015-06-16 | Google Inc. | Blended ranking of dissimilar populations using an N-furcated normalization technique |
US9423870B2 (en) | 2012-05-08 | 2016-08-23 | Google Inc. | Input determination method |
US8732560B2 (en) | 2012-05-08 | 2014-05-20 | Infineon Technologies Ag | Method and device for correction of ternary stored binary data |
WO2013169842A2 (en) | 2012-05-09 | 2013-11-14 | Yknots Industries Llc | Device, method, and graphical user interface for selecting object within a group of objects |
US8725808B2 (en) | 2012-05-10 | 2014-05-13 | Intel Mobile Communications GmbH | Method for transferring data between a first device and a second device |
JP5996262B2 (en) | 2012-05-11 | 2016-09-21 | シャープ株式会社 | CHARACTER INPUT DEVICE, ELECTRONIC DEVICE, CONTROL METHOD, CONTROL PROGRAM, AND RECORDING MEDIUM |
US9746916B2 (en) | 2012-05-11 | 2017-08-29 | Qualcomm Incorporated | Audio user interaction recognition and application interface |
US9002768B2 (en) | 2012-05-12 | 2015-04-07 | Mikhail Fedorov | Human-computer interface system |
US8897822B2 (en) | 2012-05-13 | 2014-11-25 | Wavemarket, Inc. | Auto responder |
US9280610B2 (en) | 2012-05-14 | 2016-03-08 | Apple Inc. | Crowd sourcing information to fulfill user requests |
US20130308922A1 (en) | 2012-05-15 | 2013-11-21 | Microsoft Corporation | Enhanced video discovery and productivity through accessibility |
US10417037B2 (en) | 2012-05-15 | 2019-09-17 | Apple Inc. | Systems and methods for integrating third party services with a digital assistant |
US20130307855A1 (en) | 2012-05-16 | 2013-11-21 | Mathew J. Lamb | Holographic story telling |
TWI466101B (en) | 2012-05-18 | 2014-12-21 | Asustek Comp Inc | Method and system for speech recognition |
US20120296638A1 (en) | 2012-05-18 | 2012-11-22 | Ashish Patwa | Method and system for quickly recognizing and responding to user intents and questions from natural language input using intelligent hierarchical processing and personalized adaptive semantic interface |
US9247306B2 (en) | 2012-05-21 | 2016-01-26 | Intellectual Ventures Fund 83 Llc | Forming a multimedia product using video chat |
US8484573B1 (en) | 2012-05-23 | 2013-07-09 | Google Inc. | Predictive virtual keyboard |
US8850037B2 (en) | 2012-05-24 | 2014-09-30 | Fmr Llc | Communication session transfer between devices |
US9173074B2 (en) | 2012-05-27 | 2015-10-27 | Qualcomm Incorporated | Personal hub presence and response |
US20130325436A1 (en) | 2012-05-29 | 2013-12-05 | Wright State University | Large Scale Distributed Syntactic, Semantic and Lexical Language Models |
KR20130133629A (en) | 2012-05-29 | 2013-12-09 | 삼성전자주식회사 | Method and apparatus for executing voice command in electronic device |
US9307293B2 (en) | 2012-05-30 | 2016-04-05 | Palo Alto Research Center Incorporated | Collaborative video application for remote servicing |
CN102750087A (en) | 2012-05-31 | 2012-10-24 | 华为终端有限公司 | Method, device and terminal device for controlling speech recognition function |
US20130325447A1 (en) | 2012-05-31 | 2013-12-05 | Elwha LLC, a limited liability corporation of the State of Delaware | Speech recognition adaptation systems based on adaptation data |
US8768693B2 (en) | 2012-05-31 | 2014-07-01 | Yahoo! Inc. | Automatic tag extraction from audio annotated photos |
US9620128B2 (en) | 2012-05-31 | 2017-04-11 | Elwha Llc | Speech recognition adaptation systems based on adaptation data |
US9123338B1 (en) | 2012-06-01 | 2015-09-01 | Google Inc. | Background audio identification for speech disambiguation |
US8515750B1 (en) | 2012-06-05 | 2013-08-20 | Google Inc. | Realtime acoustic adaptation using stability measures |
US8725823B2 (en) | 2012-06-05 | 2014-05-13 | Forget You Not, LLC | Location-based communications |
US10156455B2 (en) | 2012-06-05 | 2018-12-18 | Apple Inc. | Context-aware voice guidance |
US9261961B2 (en) | 2012-06-07 | 2016-02-16 | Nook Digital, Llc | Accessibility aids for users of electronic devices |
US9002380B2 (en) | 2012-06-08 | 2015-04-07 | Apple Inc. | Proximity-based notifications in a mobile device |
US9230218B2 (en) * | 2012-06-08 | 2016-01-05 | Spotify Ab | Systems and methods for recognizing ambiguity in metadata |
US9674331B2 (en) | 2012-06-08 | 2017-06-06 | Apple Inc. | Transmitting data from an automated assistant to an accessory |
US9721563B2 (en) | 2012-06-08 | 2017-08-01 | Apple Inc. | Name recognition system |
US20130332159A1 (en) | 2012-06-08 | 2013-12-12 | Apple Inc. | Using fan throttling to enhance dictation accuracy |
WO2013185109A2 (en) | 2012-06-08 | 2013-12-12 | Apple Inc. | Systems and methods for recognizing textual identifiers within a plurality of words |
US9916514B2 (en) | 2012-06-11 | 2018-03-13 | Amazon Technologies, Inc. | Text recognition driven functionality |
US9183845B1 (en) | 2012-06-12 | 2015-11-10 | Amazon Technologies, Inc. | Adjusting audio signals based on a specific frequency range associated with environmental noise characteristics |
WO2013188761A1 (en) * | 2012-06-14 | 2013-12-19 | Flextronics Ap, Llc | Methosd and system for customizing television content |
EP2862102A4 (en) * | 2012-06-14 | 2016-01-27 | Nokia Technologies Oy | Method and apparatus for associating interest tags with media items based on social diffusions among users |
US9734839B1 (en) | 2012-06-20 | 2017-08-15 | Amazon Technologies, Inc. | Routing natural language commands to the appropriate applications |
US20140012574A1 (en) | 2012-06-21 | 2014-01-09 | Maluuba Inc. | Interactive timeline for presenting and organizing tasks |
US20130346347A1 (en) | 2012-06-22 | 2013-12-26 | Google Inc. | Method to Predict a Communicative Action that is Most Likely to be Executed Given a Context |
US20130346068A1 (en) | 2012-06-25 | 2013-12-26 | Apple Inc. | Voice-Based Image Tagging and Searching |
US9813882B1 (en) | 2012-06-25 | 2017-11-07 | Amazon Technologies, Inc. | Mobile notifications based upon notification content |
US8606577B1 (en) | 2012-06-25 | 2013-12-10 | Google Inc. | Visual confirmation of voice recognized text input |
US8819841B2 (en) | 2012-06-26 | 2014-08-26 | Google Inc. | Automated accounts for media playback |
WO2014000081A1 (en) | 2012-06-26 | 2014-01-03 | Research In Motion Limited | Methods and apparatus to detect and add impact events to a calendar program |
CN102801853B (en) | 2012-06-27 | 2017-02-15 | 宇龙计算机通信科技(深圳)有限公司 | Mobile phone and method for automatically triggering task execution |
US20140006153A1 (en) | 2012-06-27 | 2014-01-02 | Infosys Limited | System for making personalized offers for business facilitation of an entity and methods thereof |
KR101961139B1 (en) | 2012-06-28 | 2019-03-25 | 엘지전자 주식회사 | Mobile terminal and method for recognizing voice thereof |
JP6050625B2 (en) | 2012-06-28 | 2016-12-21 | サターン ライセンシング エルエルシーSaturn Licensing LLC | Information processing apparatus and information processing method, computer program, and information communication system |
US9495129B2 (en) | 2012-06-29 | 2016-11-15 | Apple Inc. | Device, method, and user interface for voice-activated navigation and browsing of a document |
JP5852930B2 (en) | 2012-06-29 | 2016-02-03 | Kddi株式会社 | Input character estimation apparatus and program |
US9996628B2 (en) | 2012-06-29 | 2018-06-12 | Verisign, Inc. | Providing audio-activated resource access for user devices based on speaker voiceprint |
US9195383B2 (en) | 2012-06-29 | 2015-11-24 | Spotify Ab | Systems and methods for multi-path control signals for media presentation devices |
US10620797B2 (en) | 2012-06-29 | 2020-04-14 | Spotify Ab | Systems and methods for multi-context media control and playback |
US20140006012A1 (en) | 2012-07-02 | 2014-01-02 | Microsoft Corporation | Learning-Based Processing of Natural Language Questions |
US9536528B2 (en) | 2012-07-03 | 2017-01-03 | Google Inc. | Determining hotword suitability |
KR20140004515A (en) | 2012-07-03 | 2014-01-13 | 삼성전자주식회사 | Display apparatus, interactive server and method for providing response information |
KR101972955B1 (en) | 2012-07-03 | 2019-04-26 | 삼성전자 주식회사 | Method and apparatus for connecting service between user devices using voice |
US9064493B2 (en) | 2012-07-09 | 2015-06-23 | Nuance Communications, Inc. | Detecting potential significant errors in speech recognition results |
US20140019460A1 (en) | 2012-07-12 | 2014-01-16 | Yahoo! Inc. | Targeted search suggestions |
CN103544140A (en) | 2012-07-12 | 2014-01-29 | 国际商业机器公司 | Data processing method, display method and corresponding devices |
US9053708B2 (en) | 2012-07-18 | 2015-06-09 | International Business Machines Corporation | System, method and program product for providing automatic speech recognition (ASR) in a shared resource environment |
US20140026101A1 (en) | 2012-07-20 | 2014-01-23 | Barnesandnoble.Com Llc | Accessible Menu Navigation Techniques For Electronic Devices |
US9953584B2 (en) | 2012-07-24 | 2018-04-24 | Nook Digital, Llc | Lighting techniques for display devices |
EP2877935A4 (en) | 2012-07-25 | 2016-01-20 | Aro Inc | Using mobile device data to create a storyline, model user routine and personality, and create customized recommendation agents |
US8589911B1 (en) | 2012-07-26 | 2013-11-19 | Google Inc. | Intent fulfillment |
JP2014026629A (en) | 2012-07-26 | 2014-02-06 | Panasonic Corp | Input device and input support method |
US8442821B1 (en) | 2012-07-27 | 2013-05-14 | Google Inc. | Multi-frame prediction for hybrid neural network/hidden Markov models |
US8990343B2 (en) | 2012-07-30 | 2015-03-24 | Google Inc. | Transferring a state of an application from a first computing device to a second computing device |
US20140039893A1 (en) | 2012-07-31 | 2014-02-06 | Sri International | Personalized Voice-Driven User Interfaces for Remote Multi-User Services |
US20140035823A1 (en) | 2012-08-01 | 2014-02-06 | Apple Inc. | Dynamic Context-Based Language Determination |
US8831957B2 (en) | 2012-08-01 | 2014-09-09 | Google Inc. | Speech recognition models based on location indicia |
US9390174B2 (en) | 2012-08-08 | 2016-07-12 | Google Inc. | Search result ranking and presentation |
CN104704797B (en) | 2012-08-10 | 2018-08-10 | 纽昂斯通讯公司 | Virtual protocol communication for electronic equipment |
US10163058B2 (en) | 2012-08-14 | 2018-12-25 | Sri International | Method, system and device for inferring a mobile user's current context and proactively providing assistance |
US20140052791A1 (en) | 2012-08-14 | 2014-02-20 | International Business Machines Corporation | Task Based Filtering of Unwanted Electronic Communications |
US9031848B2 (en) | 2012-08-16 | 2015-05-12 | Nuance Communications, Inc. | User interface for searching a bundled service content data source |
US9497515B2 (en) | 2012-08-16 | 2016-11-15 | Nuance Communications, Inc. | User interface for entertainment systems |
US9292487B1 (en) | 2012-08-16 | 2016-03-22 | Amazon Technologies, Inc. | Discriminative language model pruning |
KR101922464B1 (en) | 2012-08-16 | 2018-11-27 | 삼성전자주식회사 | Method for transmitting and receiving message and an electronic device thereof |
CN107613353B (en) | 2012-08-16 | 2020-10-16 | 纽昂斯通讯公司 | Method for presenting search results on electronic device, electronic device and computer storage medium |
US20140279739A1 (en) | 2013-03-15 | 2014-09-18 | InsideSales.com, Inc. | Resolving and merging duplicate records using machine learning |
US20160357790A1 (en) | 2012-08-20 | 2016-12-08 | InsideSales.com, Inc. | Resolving and merging duplicate records using machine learning |
US9229924B2 (en) | 2012-08-24 | 2016-01-05 | Microsoft Technology Licensing, Llc | Word detection and domain dictionary recommendation |
WO2014029099A1 (en) | 2012-08-24 | 2014-02-27 | Microsoft Corporation | I-vector based clustering training data in speech recognition |
US20150227505A1 (en) | 2012-08-27 | 2015-08-13 | Hitachi, Ltd. | Word meaning relationship extraction device |
CN104584601B (en) | 2012-08-28 | 2018-10-09 | 诺基亚技术有限公司 | It was found that method and the device and system for discovery |
JP6393021B2 (en) | 2012-08-28 | 2018-09-19 | 京セラ株式会社 | Electronic device, control method, and control program |
US9026425B2 (en) | 2012-08-28 | 2015-05-05 | Xerox Corporation | Lexical and phrasal feature domain adaptation in statistical machine translation |
US9049295B1 (en) | 2012-08-28 | 2015-06-02 | West Corporation | Intelligent interactive voice response system for processing customer communications |
KR102081925B1 (en) | 2012-08-29 | 2020-02-26 | 엘지전자 주식회사 | display device and speech search method thereof |
US10026394B1 (en) | 2012-08-31 | 2018-07-17 | Amazon Technologies, Inc. | Managing dialogs on a speech recognition platform |
US9218333B2 (en) | 2012-08-31 | 2015-12-22 | Microsoft Technology Licensing, Llc | Context sensitive auto-correction |
KR101398218B1 (en) | 2012-09-03 | 2014-05-22 | 경희대학교 산학협력단 | Apparatus and method for emotional speech recognition |
US8826415B2 (en) | 2012-09-04 | 2014-09-02 | Apple Inc. | Automated device access |
WO2014036683A1 (en) * | 2012-09-04 | 2014-03-13 | 华为终端有限公司 | Media playback method, control point and terminal |
US9325809B1 (en) | 2012-09-07 | 2016-04-26 | Mindmeld, Inc. | Audio recall during voice conversations |
US9536049B2 (en) | 2012-09-07 | 2017-01-03 | Next It Corporation | Conversational virtual healthcare assistant |
US8600746B1 (en) | 2012-09-10 | 2013-12-03 | Google Inc. | Speech recognition parameter adjustment |
US20140074466A1 (en) | 2012-09-10 | 2014-03-13 | Google Inc. | Answering questions using environmental context |
US9576574B2 (en) | 2012-09-10 | 2017-02-21 | Apple Inc. | Context-sensitive handling of interruptions by intelligent digital assistant |
US20150088523A1 (en) | 2012-09-10 | 2015-03-26 | Google Inc. | Systems and Methods for Designing Voice Applications |
US20140074470A1 (en) | 2012-09-11 | 2014-03-13 | Google Inc. | Phonetic pronunciation |
US20140074472A1 (en) | 2012-09-12 | 2014-03-13 | Chih-Hung Lin | Voice control system with portable voice control device |
US20140078065A1 (en) | 2012-09-15 | 2014-03-20 | Ahmet Akkok | Predictive Keyboard With Suppressed Keys |
US9519641B2 (en) | 2012-09-18 | 2016-12-13 | Abbyy Development Llc | Photography recognition translation |
JP6057637B2 (en) | 2012-09-18 | 2017-01-11 | 株式会社アイ・オー・データ機器 | Portable information terminal device, function switching method, and function switching program |
US9081482B1 (en) | 2012-09-18 | 2015-07-14 | Google Inc. | Text input suggestion ranking |
US9547647B2 (en) | 2012-09-19 | 2017-01-17 | Apple Inc. | Voice-based media searching |
US9105268B2 (en) | 2012-09-19 | 2015-08-11 | 24/7 Customer, Inc. | Method and apparatus for predicting intent in IVR using natural language queries |
US8823507B1 (en) | 2012-09-19 | 2014-09-02 | Amazon Technologies, Inc. | Variable notification alerts |
US10042603B2 (en) | 2012-09-20 | 2018-08-07 | Samsung Electronics Co., Ltd. | Context aware service provision method and apparatus of user device |
US9076450B1 (en) | 2012-09-21 | 2015-07-07 | Amazon Technologies, Inc. | Directed audio for speech recognition |
US8983383B1 (en) | 2012-09-25 | 2015-03-17 | Rawles Llc | Providing hands-free service to multiple devices |
US9092415B2 (en) | 2012-09-25 | 2015-07-28 | Rovi Guides, Inc. | Systems and methods for automatic program recommendations based on user interactions |
US8983836B2 (en) | 2012-09-26 | 2015-03-17 | International Business Machines Corporation | Captioning using socially derived acoustic profiles |
JP2014072586A (en) | 2012-09-27 | 2014-04-21 | Sharp Corp | Display device, display method, television receiver, program, and recording medium |
US8498864B1 (en) | 2012-09-27 | 2013-07-30 | Google Inc. | Methods and systems for predicting a text |
EP2901730A4 (en) * | 2012-09-27 | 2016-08-03 | Aegis Mobility Inc | Mobile device context incorporating near field communications |
US10096316B2 (en) | 2013-11-27 | 2018-10-09 | Sri International | Sharing intents to provide virtual assistance in a multi-person dialog |
US9052964B2 (en) | 2012-09-28 | 2015-06-09 | International Business Machines Corporation | Device operability enhancement with alternative device utilization |
US10276157B2 (en) | 2012-10-01 | 2019-04-30 | Nuance Communications, Inc. | Systems and methods for providing a voice agent user interface |
US20140095172A1 (en) | 2012-10-01 | 2014-04-03 | Nuance Communications, Inc. | Systems and methods for providing a voice agent user interface |
US20140095171A1 (en) | 2012-10-01 | 2014-04-03 | Nuance Communications, Inc. | Systems and methods for providing a voice agent user interface |
US9230560B2 (en) | 2012-10-08 | 2016-01-05 | Nant Holdings Ip, Llc | Smart home automation systems and methods |
US8606568B1 (en) | 2012-10-10 | 2013-12-10 | Google Inc. | Evaluating pronouns in context |
US8543397B1 (en) | 2012-10-11 | 2013-09-24 | Google Inc. | Mobile device voice activation |
JP6066471B2 (en) | 2012-10-12 | 2017-01-25 | 本田技研工業株式会社 | Dialog system and utterance discrimination method for dialog system |
US8843845B2 (en) | 2012-10-16 | 2014-09-23 | Google Inc. | Multi-gesture text input prediction |
US20150241962A1 (en) | 2012-10-22 | 2015-08-27 | Vid Scale, Inc. | User presence detection in mobile devices |
US9319445B2 (en) | 2012-10-22 | 2016-04-19 | Spotify Ab | Systems and methods for pre-fetching media content |
US8527276B1 (en) | 2012-10-25 | 2013-09-03 | Google Inc. | Speech synthesis using deep neural networks |
US9305439B2 (en) | 2012-10-25 | 2016-04-05 | Google Inc. | Configurable indicator on computing device |
US20140122086A1 (en) | 2012-10-26 | 2014-05-01 | Microsoft Corporation | Augmenting speech recognition with depth imaging |
US20150228274A1 (en) | 2012-10-26 | 2015-08-13 | Nokia Technologies Oy | Multi-Device Speech Recognition |
US9459176B2 (en) * | 2012-10-26 | 2016-10-04 | Azima Holdings, Inc. | Voice controlled vibration data analyzer systems and methods |
KR101967917B1 (en) | 2012-10-30 | 2019-08-13 | 삼성전자주식회사 | Apparatas and method for recognizing a voice in an electronic device |
US10304465B2 (en) | 2012-10-30 | 2019-05-28 | Google Technology Holdings LLC | Voice control user interface for low power mode |
WO2014070872A2 (en) | 2012-10-30 | 2014-05-08 | Robert Bosch Gmbh | System and method for multimodal interaction with reduced distraction in operating vehicles |
WO2014071043A1 (en) | 2012-10-31 | 2014-05-08 | DoWhatILikeBest, LLC | Favorite and serendipitous event correlation and notification |
US9734151B2 (en) | 2012-10-31 | 2017-08-15 | Tivo Solutions Inc. | Method and system for voice based media search |
US8606576B1 (en) | 2012-11-02 | 2013-12-10 | Google Inc. | Communication log with extracted keywords from speech-to-text processing |
US9093069B2 (en) | 2012-11-05 | 2015-07-28 | Nuance Communications, Inc. | Privacy-sensitive speech model creation via aggregation of multiple user models |
JP6018881B2 (en) | 2012-11-07 | 2016-11-02 | 株式会社日立製作所 | Navigation device and navigation method |
US20140136987A1 (en) | 2012-11-09 | 2014-05-15 | Apple Inc. | Generation of a user interface based on contacts |
US9275642B2 (en) | 2012-11-13 | 2016-03-01 | Unified Computer Intelligence Corporation | Voice-operated internet-ready ubiquitous computing device and method thereof |
KR20140060995A (en) | 2012-11-13 | 2014-05-21 | 삼성전자주식회사 | Rejection message providing method based on a situation and electronic device supporting the same |
US9247387B2 (en) | 2012-11-13 | 2016-01-26 | International Business Machines Corporation | Proximity based reminders |
KR20140061803A (en) | 2012-11-14 | 2014-05-22 | 삼성전자주식회사 | Projection apparatus |
US9235321B2 (en) | 2012-11-14 | 2016-01-12 | Facebook, Inc. | Animation sequence associated with content item |
KR101709187B1 (en) | 2012-11-14 | 2017-02-23 | 한국전자통신연구원 | Spoken Dialog Management System Based on Dual Dialog Management using Hierarchical Dialog Task Library |
US9798799B2 (en) | 2012-11-15 | 2017-10-24 | Sri International | Vehicle personal assistant that interprets spoken natural language input based upon vehicle context |
US9085303B2 (en) | 2012-11-15 | 2015-07-21 | Sri International | Vehicle personal assistant |
US9032219B2 (en) | 2012-11-16 | 2015-05-12 | Nuance Communications, Inc. | Securing speech recognition data |
US8965754B2 (en) | 2012-11-20 | 2015-02-24 | International Business Machines Corporation | Text prediction using environment hints |
JP2014102669A (en) | 2012-11-20 | 2014-06-05 | Toshiba Corp | Information processor, information processing method and program |
US10551928B2 (en) | 2012-11-20 | 2020-02-04 | Samsung Electronics Company, Ltd. | GUI transitions on wearable electronic device |
WO2014078965A1 (en) | 2012-11-22 | 2014-05-30 | 8303142 Canada Inc. | System and method for managing several mobile devices simultaneously |
US9875741B2 (en) | 2013-03-15 | 2018-01-23 | Google Llc | Selective speech recognition for chat and digital personal assistant systems |
US10026400B2 (en) | 2013-06-27 | 2018-07-17 | Google Llc | Generating dialog recommendations for chat information systems based on user interaction and environmental data |
US20140146200A1 (en) | 2012-11-28 | 2014-05-29 | Research In Motion Limited | Entries to an electronic calendar |
RU2530268C2 (en) | 2012-11-28 | 2014-10-10 | Общество с ограниченной ответственностью "Спиктуит" | Method for user training of information dialogue system |
CA2892664C (en) | 2012-11-29 | 2020-01-21 | Edsense, L.L.C. | System and method for displaying multiple applications |
JP2014109889A (en) | 2012-11-30 | 2014-06-12 | Toshiba Corp | Content retrieval device, content retrieval method and control program |
US9589149B2 (en) | 2012-11-30 | 2017-03-07 | Microsoft Technology Licensing, Llc | Combining personalization and privacy locally on devices |
US9549323B2 (en) | 2012-12-03 | 2017-01-17 | Samsung Electronics Co., Ltd. | Method and mobile terminal for controlling screen lock |
US9159319B1 (en) | 2012-12-03 | 2015-10-13 | Amazon Technologies, Inc. | Keyword spotting with competitor models |
US9819786B2 (en) | 2012-12-05 | 2017-11-14 | Facebook, Inc. | Systems and methods for a symbol-adaptable keyboard |
US9026429B2 (en) | 2012-12-05 | 2015-05-05 | Facebook, Inc. | Systems and methods for character string auto-suggestion based on degree of difficulty |
US9244905B2 (en) | 2012-12-06 | 2016-01-26 | Microsoft Technology Licensing, Llc | Communication context based predictive-text suggestion |
US8930181B2 (en) | 2012-12-06 | 2015-01-06 | Prashant Parikh | Automatic dynamic contextual data entry completion |
US20140164476A1 (en) | 2012-12-06 | 2014-06-12 | At&T Intellectual Property I, Lp | Apparatus and method for providing a virtual assistant |
US20140163951A1 (en) | 2012-12-07 | 2014-06-12 | Xerox Corporation | Hybrid adaptation of named entity recognition |
US9471559B2 (en) | 2012-12-10 | 2016-10-18 | International Business Machines Corporation | Deep analysis of natural language questions for question answering system |
KR102091003B1 (en) | 2012-12-10 | 2020-03-19 | 삼성전자 주식회사 | Method and apparatus for providing context aware service using speech recognition |
US9697827B1 (en) | 2012-12-11 | 2017-07-04 | Amazon Technologies, Inc. | Error reduction in speech processing |
US9659298B2 (en) | 2012-12-11 | 2017-05-23 | Nuance Communications, Inc. | Systems and methods for informing virtual agent recommendation |
US20140164532A1 (en) | 2012-12-11 | 2014-06-12 | Nuance Communications, Inc. | Systems and methods for virtual agent participation in multiparty conversation |
US9679300B2 (en) | 2012-12-11 | 2017-06-13 | Nuance Communications, Inc. | Systems and methods for virtual agent recommendation for multiple persons |
US9148394B2 (en) | 2012-12-11 | 2015-09-29 | Nuance Communications, Inc. | Systems and methods for user interface presentation of virtual agent |
US9117450B2 (en) | 2012-12-12 | 2015-08-25 | Nuance Communications, Inc. | Combining re-speaking, partial agent transcription and ASR for improved accuracy / human guided ASR |
US9190057B2 (en) | 2012-12-12 | 2015-11-17 | Amazon Technologies, Inc. | Speech model retrieval in distributed speech recognition systems |
KR102014778B1 (en) | 2012-12-14 | 2019-08-27 | 엘지전자 주식회사 | Digital device for providing text messaging service and the method for controlling the same |
US9141660B2 (en) | 2012-12-17 | 2015-09-22 | International Business Machines Corporation | Intelligent evidence classification and notification in a deep question answering system |
EP2938022A4 (en) | 2012-12-18 | 2016-08-24 | Samsung Electronics Co Ltd | Method and device for controlling home device remotely in home network system |
US9070366B1 (en) | 2012-12-19 | 2015-06-30 | Amazon Technologies, Inc. | Architecture for multi-domain utterance processing |
US9098467B1 (en) | 2012-12-19 | 2015-08-04 | Rawles Llc | Accepting voice commands based on user identity |
US8977555B2 (en) | 2012-12-20 | 2015-03-10 | Amazon Technologies, Inc. | Identification of utterance subjects |
US8645138B1 (en) | 2012-12-20 | 2014-02-04 | Google Inc. | Two-pass decoding for speech recognition of search and action requests |
WO2014096506A1 (en) | 2012-12-21 | 2014-06-26 | Nokia Corporation | Method, apparatus, and computer program product for personalizing speech recognition |
KR20140082157A (en) | 2012-12-24 | 2014-07-02 | 한국전자통신연구원 | Apparatus for speech recognition using multiple acoustic model and method thereof |
JP2014126600A (en) | 2012-12-25 | 2014-07-07 | Panasonic Corp | Voice recognition device, voice recognition method and television |
JP2014124332A (en) | 2012-12-26 | 2014-07-07 | Daiichi Shokai Co Ltd | Game machine |
CN103020047A (en) | 2012-12-31 | 2013-04-03 | 威盛电子股份有限公司 | Method for revising voice response and natural language dialogue system |
CN103049567A (en) * | 2012-12-31 | 2013-04-17 | 威盛电子股份有限公司 | Retrieval method, retrieval system and natural language understanding system |
US8571851B1 (en) | 2012-12-31 | 2013-10-29 | Google Inc. | Semantic interpretation using user gaze order |
KR101892734B1 (en) | 2013-01-04 | 2018-08-28 | 한국전자통신연구원 | Method and apparatus for correcting error of recognition in speech recognition system |
KR20140093303A (en) | 2013-01-07 | 2014-07-28 | 삼성전자주식회사 | display apparatus and method for controlling the display apparatus |
KR20140089862A (en) | 2013-01-07 | 2014-07-16 | 삼성전자주식회사 | display apparatus and method for controlling the display apparatus |
US20140195233A1 (en) | 2013-01-08 | 2014-07-10 | Spansion Llc | Distributed Speech Recognition System |
DE112013006384T5 (en) | 2013-01-09 | 2015-09-24 | Mitsubishi Electric Corporation | Speech recognition device and display method |
US20140198047A1 (en) | 2013-01-14 | 2014-07-17 | Nuance Communications, Inc. | Reducing error rates for touch based keyboards |
US8731912B1 (en) | 2013-01-16 | 2014-05-20 | Google Inc. | Delaying audio notifications |
US9292489B1 (en) | 2013-01-16 | 2016-03-22 | Google Inc. | Sub-lexical language models with word level pronunciation lexicons |
US8942674B2 (en) | 2013-01-18 | 2015-01-27 | Blackberry Limited | Responding to incoming calls |
US9047274B2 (en) | 2013-01-21 | 2015-06-02 | Xerox Corporation | Machine translation-driven authoring system and method |
US20140203939A1 (en) | 2013-01-21 | 2014-07-24 | Rtc Inc. | Control and monitoring of light-emitting-diode (led) bulbs |
US9148499B2 (en) | 2013-01-22 | 2015-09-29 | Blackberry Limited | Method and system for automatically identifying voice tags through user operation |
EP2760015A1 (en) | 2013-01-23 | 2014-07-30 | BlackBerry Limited | Event-triggered hands-free multitasking for media playback |
US9530409B2 (en) | 2013-01-23 | 2016-12-27 | Blackberry Limited | Event-triggered hands-free multitasking for media playback |
US9165566B2 (en) | 2013-01-24 | 2015-10-20 | Microsoft Technology Licensing, Llc | Indefinite speech inputs |
DE102013001219B4 (en) | 2013-01-25 | 2019-08-29 | Inodyn Newmedia Gmbh | Method and system for voice activation of a software agent from a standby mode |
JP6251958B2 (en) | 2013-01-28 | 2017-12-27 | 富士通株式会社 | Utterance analysis device, voice dialogue control device, method, and program |
JP2014150323A (en) | 2013-01-31 | 2014-08-21 | Sharp Corp | Character input device |
KR20140098947A (en) | 2013-01-31 | 2014-08-11 | 삼성전자주식회사 | User terminal, advertisement providing system and method thereof |
US10055091B2 (en) | 2013-02-01 | 2018-08-21 | Microsoft Technology Licensing, Llc | Autosave and manual save modes for software applications |
US8694315B1 (en) | 2013-02-05 | 2014-04-08 | Visa International Service Association | System and method for authentication using speaker verification techniques and fraud model |
US20140218372A1 (en) | 2013-02-05 | 2014-08-07 | Apple Inc. | Intelligent digital assistant in a desktop environment |
KR102118209B1 (en) | 2013-02-07 | 2020-06-02 | 애플 인크. | Voice trigger for a digital assistant |
US20140223481A1 (en) * | 2013-02-07 | 2014-08-07 | United Video Properties, Inc. | Systems and methods for updating a search request |
US9842489B2 (en) | 2013-02-14 | 2017-12-12 | Google Llc | Waking other devices for additional data |
US9408040B2 (en) | 2013-02-14 | 2016-08-02 | Fuji Xerox Co., Ltd. | Systems and methods for room-level location using WiFi |
US9791921B2 (en) * | 2013-02-19 | 2017-10-17 | Microsoft Technology Licensing, Llc | Context-aware augmented reality object commands |
US10078437B2 (en) | 2013-02-20 | 2018-09-18 | Blackberry Limited | Method and apparatus for responding to a notification via a capacitive physical keyboard |
US9734819B2 (en) | 2013-02-21 | 2017-08-15 | Google Technology Holdings LLC | Recognizing accented speech |
US20140236986A1 (en) | 2013-02-21 | 2014-08-21 | Apple Inc. | Natural language document search |
US9621619B2 (en) | 2013-02-21 | 2017-04-11 | International Business Machines Corporation | Enhanced notification for relevant communications |
US9414004B2 (en) * | 2013-02-22 | 2016-08-09 | The Directv Group, Inc. | Method for combining voice signals to form a continuous conversation in performing a voice search |
US20140245140A1 (en) | 2013-02-22 | 2014-08-28 | Next It Corporation | Virtual Assistant Transfer between Smart Devices |
US9484023B2 (en) | 2013-02-22 | 2016-11-01 | International Business Machines Corporation | Conversion of non-back-off language models for efficient speech decoding |
US9672822B2 (en) | 2013-02-22 | 2017-06-06 | Next It Corporation | Interaction with a portion of a content item through a virtual assistant |
US9172747B2 (en) | 2013-02-25 | 2015-10-27 | Artificial Solutions Iberia SL | System and methods for virtual assistant networks |
US20140304086A1 (en) * | 2013-02-25 | 2014-10-09 | Turn Inc. | Methods and systems for modeling campaign goal adjustment |
US9330659B2 (en) | 2013-02-25 | 2016-05-03 | Microsoft Technology Licensing, Llc | Facilitating development of a spoken natural language interface |
US9865266B2 (en) | 2013-02-25 | 2018-01-09 | Nuance Communications, Inc. | Method and apparatus for automated speaker parameters adaptation in a deployed speaker verification system |
KR101383552B1 (en) | 2013-02-25 | 2014-04-10 | 미디어젠(주) | Speech recognition method of sentence having multiple instruction |
US9280981B2 (en) | 2013-02-27 | 2016-03-08 | Blackberry Limited | Method and apparatus for voice control of a mobile device |
US10354677B2 (en) | 2013-02-28 | 2019-07-16 | Nuance Communications, Inc. | System and method for identification of intent segment(s) in caller-agent conversations |
US9218819B1 (en) | 2013-03-01 | 2015-12-22 | Google Inc. | Customizing actions based on contextual data and voice-based inputs |
US9251467B2 (en) | 2013-03-03 | 2016-02-02 | Microsoft Technology Licensing, Llc | Probabilistic parsing |
US9460715B2 (en) * | 2013-03-04 | 2016-10-04 | Amazon Technologies, Inc. | Identification using audio signatures and additional characteristics |
US9554050B2 (en) | 2013-03-04 | 2017-01-24 | Apple Inc. | Mobile device using images and location for reminders |
US9293129B2 (en) | 2013-03-05 | 2016-03-22 | Microsoft Technology Licensing, Llc | Speech recognition assisted evaluation on text-to-speech pronunciation issue detection |
US9454957B1 (en) | 2013-03-05 | 2016-09-27 | Amazon Technologies, Inc. | Named entity resolution in spoken language processing |
KR101952179B1 (en) | 2013-03-05 | 2019-05-22 | 엘지전자 주식회사 | Mobile terminal and control method for the mobile terminal |
US10795528B2 (en) | 2013-03-06 | 2020-10-06 | Nuance Communications, Inc. | Task assistant having multiple visual displays |
CN104038621A (en) | 2013-03-06 | 2014-09-10 | 三星电子(中国)研发中心 | Device and method for managing event information in communication terminal |
US9990611B2 (en) | 2013-03-08 | 2018-06-05 | Baydin, Inc. | Systems and methods for incorporating calendar functionality into electronic messages |
US20140257902A1 (en) | 2013-03-08 | 2014-09-11 | Baydin, Inc. | Systems and methods for incorporating calendar functionality into electronic messages |
US9496968B2 (en) | 2013-03-08 | 2016-11-15 | Google Inc. | Proximity detection by mobile devices |
US9361885B2 (en) | 2013-03-12 | 2016-06-07 | Nuance Communications, Inc. | Methods and apparatus for detecting a voice command |
US9112984B2 (en) | 2013-03-12 | 2015-08-18 | Nuance Communications, Inc. | Methods and apparatus for detecting a voice command |
US9076459B2 (en) | 2013-03-12 | 2015-07-07 | Intermec Ip, Corp. | Apparatus and method to classify sound to detect speech |
US11393461B2 (en) | 2013-03-12 | 2022-07-19 | Cerence Operating Company | Methods and apparatus for detecting a voice command |
US9129013B2 (en) | 2013-03-12 | 2015-09-08 | Nuance Communications, Inc. | Methods and apparatus for entity detection |
US10229697B2 (en) | 2013-03-12 | 2019-03-12 | Google Technology Holdings LLC | Apparatus and method for beamforming to obtain voice and noise signals |
EP2946383B1 (en) | 2013-03-12 | 2020-02-26 | Nuance Communications, Inc. | Methods and apparatus for detecting a voice command |
US9477753B2 (en) | 2013-03-12 | 2016-10-25 | International Business Machines Corporation | Classifier-based system combination for spoken term detection |
US9378739B2 (en) | 2013-03-13 | 2016-06-28 | Nuance Communications, Inc. | Identifying corresponding positions in different representations of a textual work |
US9135248B2 (en) * | 2013-03-13 | 2015-09-15 | Arris Technology, Inc. | Context demographic determination system |
US9282423B2 (en) | 2013-03-13 | 2016-03-08 | Aliphcom | Proximity and interface controls of media devices for media presentations |
US10219100B2 (en) | 2013-03-13 | 2019-02-26 | Aliphcom | Determining proximity for devices interacting with media devices |
US20140274005A1 (en) | 2013-03-13 | 2014-09-18 | Aliphcom | Intelligent connection management in wireless devices |
KR20140112910A (en) | 2013-03-14 | 2014-09-24 | 삼성전자주식회사 | Input controlling Method and Electronic Device supporting the same |
US20140278349A1 (en) | 2013-03-14 | 2014-09-18 | Microsoft Corporation | Language Model Dictionaries for Text Predictions |
US10572476B2 (en) | 2013-03-14 | 2020-02-25 | Apple Inc. | Refining a search based on schedule items |
US9842584B1 (en) | 2013-03-14 | 2017-12-12 | Amazon Technologies, Inc. | Providing content on multiple devices |
US9189196B2 (en) | 2013-03-14 | 2015-11-17 | Google Inc. | Compartmentalized self registration of external devices |
US9733821B2 (en) | 2013-03-14 | 2017-08-15 | Apple Inc. | Voice control to diagnose inadvertent activation of accessibility features |
US20140267599A1 (en) | 2013-03-14 | 2014-09-18 | 360Brandvision, Inc. | User interaction with a holographic poster via a secondary mobile device |
US9123345B2 (en) | 2013-03-14 | 2015-09-01 | Honda Motor Co., Ltd. | Voice interface systems and methods |
US9317585B2 (en) | 2013-03-15 | 2016-04-19 | Google Inc. | Search query suggestions based on personal information |
US10638198B2 (en) | 2013-03-15 | 2020-04-28 | Ebay Inc. | Shoppable video |
WO2014144579A1 (en) | 2013-03-15 | 2014-09-18 | Apple Inc. | System and method for updating an adaptive speech recognition model |
AU2014233517B2 (en) | 2013-03-15 | 2017-05-25 | Apple Inc. | Training an at least partial voice command system |
US9201865B2 (en) | 2013-03-15 | 2015-12-01 | Bao Tran | Automated assistance for user request that determines semantics by domain, task, and parameter |
CN105144133B (en) | 2013-03-15 | 2020-11-20 | 苹果公司 | Context-sensitive handling of interrupts |
WO2014143959A2 (en) | 2013-03-15 | 2014-09-18 | Bodhi Technology Ventures Llc | Volume control for mobile device using a wireless device |
US9378065B2 (en) | 2013-03-15 | 2016-06-28 | Advanced Elemental Technologies, Inc. | Purposeful computing |
US20140282203A1 (en) | 2013-03-15 | 2014-09-18 | Research In Motion Limited | System and method for predictive text input |
US20160132046A1 (en) | 2013-03-15 | 2016-05-12 | Fisher-Rosemount Systems, Inc. | Method and apparatus for controlling a process plant with wearable mobile control devices |
US9299041B2 (en) * | 2013-03-15 | 2016-03-29 | Business Objects Software Ltd. | Obtaining data from unstructured data for a structured data collection |
US9558743B2 (en) | 2013-03-15 | 2017-01-31 | Google Inc. | Integration of semantic context information |
EP2973315A4 (en) | 2013-03-15 | 2016-11-16 | Adityo Prakash | Systems and methods for facilitating integrated behavioral support |
US9886160B2 (en) | 2013-03-15 | 2018-02-06 | Google Llc | Managing audio at the tab level for user notification and control |
US11151899B2 (en) | 2013-03-15 | 2021-10-19 | Apple Inc. | User training by intelligent digital assistant |
US9176649B2 (en) | 2013-03-15 | 2015-11-03 | American Megatrends, Inc. | Method and apparatus of remote management of computer system using voice and gesture based input |
WO2014139173A1 (en) | 2013-03-15 | 2014-09-18 | Google Inc. | Virtual keyboard input for international languages |
US9189157B2 (en) | 2013-03-15 | 2015-11-17 | Blackberry Limited | Method and apparatus for word prediction selection |
US9479499B2 (en) | 2013-03-21 | 2016-10-25 | Tencent Technology (Shenzhen) Company Limited | Method and apparatus for identity authentication via mobile capturing code |
JP6221301B2 (en) | 2013-03-28 | 2017-11-01 | 富士通株式会社 | Audio processing apparatus, audio processing system, and audio processing method |
CN103236260B (en) | 2013-03-29 | 2015-08-12 | 京东方科技集团股份有限公司 | Speech recognition system |
US20140297288A1 (en) | 2013-03-29 | 2014-10-02 | Orange | Telephone voice personal assistant |
JP2014203207A (en) | 2013-04-03 | 2014-10-27 | ソニー株式会社 | Information processing unit, information processing method, and computer program |
US9300718B2 (en) | 2013-04-09 | 2016-03-29 | Avaya Inc. | System and method for keyword-based notification and delivery of content |
CN103198831A (en) | 2013-04-10 | 2013-07-10 | 威盛电子股份有限公司 | Voice control method and mobile terminal device |
US10027723B2 (en) | 2013-04-12 | 2018-07-17 | Provenance Asset Group Llc | Method and apparatus for initiating communication and sharing of content among a plurality of devices |
US10564815B2 (en) | 2013-04-12 | 2020-02-18 | Nant Holdings Ip, Llc | Virtual teller systems and methods |
US8825474B1 (en) | 2013-04-16 | 2014-09-02 | Google Inc. | Text suggestion output using past interaction data |
US9875494B2 (en) | 2013-04-16 | 2018-01-23 | Sri International | Using intents to analyze and personalize a user's dialog experience with a virtual personal assistant |
US20150193392A1 (en) | 2013-04-17 | 2015-07-09 | Google Inc. | User Interface for Quickly Checking Agenda and Creating New Events |
US9760644B2 (en) | 2013-04-17 | 2017-09-12 | Google Inc. | Embedding event creation link in a document |
NL2010662C2 (en) | 2013-04-18 | 2014-10-21 | Bosch Gmbh Robert | Remote maintenance. |
US10445115B2 (en) | 2013-04-18 | 2019-10-15 | Verint Americas Inc. | Virtual assistant focused user interfaces |
US9177318B2 (en) | 2013-04-22 | 2015-11-03 | Palo Alto Research Center Incorporated | Method and apparatus for customizing conversation agents based on user characteristics using a relevance score for automatic statements, and a response prediction function |
US9075435B1 (en) | 2013-04-22 | 2015-07-07 | Amazon Technologies, Inc. | Context-aware notifications |
CN103280217B (en) | 2013-05-02 | 2016-05-04 | 锤子科技(北京)有限公司 | A kind of audio recognition method of mobile terminal and device thereof |
US9384751B2 (en) | 2013-05-06 | 2016-07-05 | Honeywell International Inc. | User authentication of voice controlled devices |
US9472205B2 (en) | 2013-05-06 | 2016-10-18 | Honeywell International Inc. | Device voice recognition systems and methods |
US9064495B1 (en) | 2013-05-07 | 2015-06-23 | Amazon Technologies, Inc. | Measurement of user perceived latency in a cloud based speech application |
KR20140132246A (en) | 2013-05-07 | 2014-11-17 | 삼성전자주식회사 | Object selection method and object selection apparatus |
US9223898B2 (en) | 2013-05-08 | 2015-12-29 | Facebook, Inc. | Filtering suggested structured queries on online social networks |
US9923849B2 (en) | 2013-05-09 | 2018-03-20 | Ebay Inc. | System and method for suggesting a phrase based on a context |
EP2801974A3 (en) | 2013-05-09 | 2015-02-18 | DSP Group Ltd. | Low power activation of a voice activated device |
US9489625B2 (en) | 2013-05-10 | 2016-11-08 | Sri International | Rapid development of virtual personal assistant applications |
US9081411B2 (en) | 2013-05-10 | 2015-07-14 | Sri International | Rapid development of virtual personal assistant applications |
US20140337751A1 (en) | 2013-05-13 | 2014-11-13 | Microsoft Corporation | Automatic creation of calendar items |
US9514470B2 (en) | 2013-05-16 | 2016-12-06 | Microsoft Technology Licensing, Llc | Enhanced search suggestion for personal information services |
KR101334342B1 (en) | 2013-05-16 | 2013-11-29 | 주식회사 네오패드 | Apparatus and method for inputting character |
KR101825963B1 (en) | 2013-05-16 | 2018-02-06 | 인텔 코포레이션 | Techniques for natural user interface input based on context |
US9495266B2 (en) | 2013-05-16 | 2016-11-15 | Advantest Corporation | Voice recognition virtual test engineering assistant |
US9432499B2 (en) | 2013-05-18 | 2016-08-30 | Loralee Hajdu | Peripheral specific selection of automated response messages |
CN105122353B (en) | 2013-05-20 | 2019-07-09 | 英特尔公司 | The method of speech recognition for the computing device of speech recognition and on computing device |
US20150199077A1 (en) | 2013-05-23 | 2015-07-16 | Google Inc. | Scheduling and viewing a calender event using time zones based on a user's location at event time |
US9747900B2 (en) | 2013-05-24 | 2017-08-29 | Google Technology Holdings LLC | Method and apparatus for using image data to aid voice recognition |
US20140351760A1 (en) | 2013-05-24 | 2014-11-27 | Google Inc. | Order-independent text input |
US20140350933A1 (en) | 2013-05-24 | 2014-11-27 | Samsung Electronics Co., Ltd. | Voice recognition apparatus and control method thereof |
US20140358523A1 (en) | 2013-05-30 | 2014-12-04 | Wright State University | Topic-specific sentiment extraction |
US20140358519A1 (en) | 2013-06-03 | 2014-12-04 | Xerox Corporation | Confidence-driven rewriting of source texts for improved translation |
US9286029B2 (en) | 2013-06-06 | 2016-03-15 | Honda Motor Co., Ltd. | System and method for multimodal human-vehicle interaction and belief tracking |
KR102197560B1 (en) | 2013-06-07 | 2020-12-31 | 애플 인크. | Intelligent automated assistant |
US9267805B2 (en) | 2013-06-07 | 2016-02-23 | Apple Inc. | Modeling significant locations |
WO2014197334A2 (en) | 2013-06-07 | 2014-12-11 | Apple Inc. | System and method for user-specified pronunciation of words for speech synthesis and recognition |
WO2014197336A1 (en) | 2013-06-07 | 2014-12-11 | Apple Inc. | System and method for detecting errors in interactions with a voice-based digital assistant |
US9582608B2 (en) | 2013-06-07 | 2017-02-28 | Apple Inc. | Unified ranking with entropy-weighted information for phrase-based semantic auto-completion |
WO2014197335A1 (en) | 2013-06-08 | 2014-12-11 | Apple Inc. | Interpreting and acting upon commands that involve sharing information with remote devices |
US9495620B2 (en) | 2013-06-09 | 2016-11-15 | Apple Inc. | Multi-script handwriting recognition using a universal recognizer |
US10176167B2 (en) | 2013-06-09 | 2019-01-08 | Apple Inc. | System and method for inferring user intent from speech inputs |
US10481769B2 (en) | 2013-06-09 | 2019-11-19 | Apple Inc. | Device, method, and graphical user interface for providing navigation and search functionalities |
KR101959188B1 (en) | 2013-06-09 | 2019-07-02 | 애플 인크. | Device, method, and graphical user interface for enabling conversation persistence across two or more instances of a digital assistant |
KR20140144104A (en) | 2013-06-10 | 2014-12-18 | 삼성전자주식회사 | Electronic apparatus and Method for providing service thereof |
US9449600B2 (en) | 2013-06-11 | 2016-09-20 | Plantronics, Inc. | Character data entry |
US9892115B2 (en) | 2013-06-11 | 2018-02-13 | Facebook, Inc. | Translation training with cross-lingual multi-media support |
US9508040B2 (en) | 2013-06-12 | 2016-11-29 | Microsoft Technology Licensing, Llc | Predictive pre-launch for applications |
CN105265005B (en) | 2013-06-13 | 2019-09-17 | 苹果公司 | System and method for the urgent call initiated by voice command |
CN103292437B (en) | 2013-06-17 | 2016-01-20 | 广东美的制冷设备有限公司 | Voice interactive air conditioner and control method thereof |
US9728184B2 (en) | 2013-06-18 | 2017-08-08 | Microsoft Technology Licensing, Llc | Restructuring deep neural network acoustic models |
US9437186B1 (en) | 2013-06-19 | 2016-09-06 | Amazon Technologies, Inc. | Enhanced endpoint detection for speech recognition |
USRE49014E1 (en) | 2013-06-19 | 2022-04-05 | Panasonic Intellectual Property Corporation Of America | Voice interaction method, and device |
US9633317B2 (en) | 2013-06-20 | 2017-04-25 | Viv Labs, Inc. | Dynamically evolving cognitive architecture system based on a natural language intent interpreter |
KR20140147587A (en) | 2013-06-20 | 2014-12-30 | 한국전자통신연구원 | A method and apparatus to detect speech endpoint using weighted finite state transducer |
US20140379334A1 (en) | 2013-06-20 | 2014-12-25 | Qnx Software Systems Limited | Natural language understanding automatic speech recognition post processing |
KR102160767B1 (en) | 2013-06-20 | 2020-09-29 | 삼성전자주식회사 | Mobile terminal and method for detecting a gesture to control functions |
US9311298B2 (en) | 2013-06-21 | 2016-04-12 | Microsoft Technology Licensing, Llc | Building conversational understanding systems using a toolset |
US10496743B2 (en) | 2013-06-26 | 2019-12-03 | Nuance Communications, Inc. | Methods and apparatus for extracting facts from a medical text |
US20150006148A1 (en) | 2013-06-27 | 2015-01-01 | Microsoft Corporation | Automatically Creating Training Data For Language Identifiers |
US8947596B2 (en) | 2013-06-27 | 2015-02-03 | Intel Corporation | Alignment of closed captions |
US9747899B2 (en) | 2013-06-27 | 2017-08-29 | Amazon Technologies, Inc. | Detecting self-generated wake expressions |
EP3014610B1 (en) | 2013-06-28 | 2023-10-04 | Harman International Industries, Incorporated | Wireless control of linked devices |
US9741339B2 (en) | 2013-06-28 | 2017-08-22 | Google Inc. | Data driven word pronunciation learning and scoring with crowd sourcing based on the word's phonemes pronunciation scores |
US9646606B2 (en) | 2013-07-03 | 2017-05-09 | Google Inc. | Speech recognition using domain knowledge |
JP6102588B2 (en) | 2013-07-10 | 2017-03-29 | ソニー株式会社 | Information processing apparatus, information processing method, and program |
CN103365279A (en) | 2013-07-10 | 2013-10-23 | 崔海伟 | State detecting device and system and method for feeding back states of intelligent home system |
DE102014109121B4 (en) | 2013-07-10 | 2023-05-04 | Gm Global Technology Operations, Llc | Systems and methods for arbitration of a speech dialog service |
US9396727B2 (en) | 2013-07-10 | 2016-07-19 | GM Global Technology Operations LLC | Systems and methods for spoken dialog service arbitration |
US9445209B2 (en) | 2013-07-11 | 2016-09-13 | Intel Corporation | Mechanism and apparatus for seamless voice wake and speaker verification |
WO2015006196A1 (en) | 2013-07-11 | 2015-01-15 | Mophie, Inc. | Method and system for communicatively coupling a wearable computer with one or more non-wearable computers |
TWI508057B (en) | 2013-07-15 | 2015-11-11 | Chunghwa Picture Tubes Ltd | Speech recognition system and method |
US9311912B1 (en) | 2013-07-22 | 2016-04-12 | Amazon Technologies, Inc. | Cost efficient distributed text-to-speech processing |
US9407950B2 (en) | 2013-07-23 | 2016-08-02 | Microsoft Technology Licensing, Llc | Controlling devices in entertainment environment |
US20150032238A1 (en) | 2013-07-23 | 2015-01-29 | Motorola Mobility Llc | Method and Device for Audio Input Routing |
US9335983B2 (en) | 2013-07-28 | 2016-05-10 | Oded Haim Breiner | Method and system for displaying a non-installed android application and for requesting an action from a non-installed android application |
US9311915B2 (en) | 2013-07-31 | 2016-04-12 | Google Inc. | Context-based speech recognition |
US9575720B2 (en) | 2013-07-31 | 2017-02-21 | Google Inc. | Visual confirmation for a recognized voice-initiated action |
US20150039606A1 (en) | 2013-08-01 | 2015-02-05 | Vamsi Krishna Salaka | Search phrase modification |
TWI601032B (en) | 2013-08-02 | 2017-10-01 | 晨星半導體股份有限公司 | Controller for voice-controlled device and associated method |
CN105493511A (en) | 2013-08-06 | 2016-04-13 | 萨罗尼科斯贸易与服务一人有限公司 | System for controlling electronic devices by means of voice commands, more specifically a remote control to control a plurality of electronic devices by means of voice commands |
CN105453026A (en) | 2013-08-06 | 2016-03-30 | 苹果公司 | Auto-activating smart responses based on activities from remote devices |
KR20150020872A (en) * | 2013-08-19 | 2015-02-27 | 현대자동차주식회사 | Control device and control method for function control of car |
JP2015041845A (en) | 2013-08-21 | 2015-03-02 | カシオ計算機株式会社 | Character input device and program |
US10047970B2 (en) | 2013-08-21 | 2018-08-14 | Honeywell International Inc. | Devices and methods for interacting with an HVAC controller |
EP2862164B1 (en) | 2013-08-23 | 2017-05-31 | Nuance Communications, Inc. | Multiple pass automatic speech recognition |
WO2015030474A1 (en) | 2013-08-26 | 2015-03-05 | 삼성전자 주식회사 | Electronic device and method for voice recognition |
KR102147935B1 (en) | 2013-08-29 | 2020-08-25 | 삼성전자주식회사 | Method for processing data and an electronic device thereof |
MY175230A (en) | 2013-08-29 | 2020-06-16 | Panasonic Ip Corp America | Device control method, display control method, and purchase payment method |
WO2015030796A1 (en) | 2013-08-30 | 2015-03-05 | Intel Corporation | Extensible context-aware natural language interactions for virtual personal assistants |
US20150066506A1 (en) | 2013-08-30 | 2015-03-05 | Verint Systems Ltd. | System and Method of Text Zoning |
US10867597B2 (en) | 2013-09-02 | 2020-12-15 | Microsoft Technology Licensing, Llc | Assignment of semantic labels to a sequence of words using neural network architectures |
US9316400B2 (en) | 2013-09-03 | 2016-04-19 | Panasonic Intellctual Property Corporation of America | Appliance control method, speech-based appliance control system, and cooking appliance |
US9633669B2 (en) | 2013-09-03 | 2017-04-25 | Amazon Technologies, Inc. | Smart circular audio buffer |
KR102065409B1 (en) | 2013-09-04 | 2020-01-13 | 엘지전자 주식회사 | Mobile terminal and method for controlling the same |
GB2517952B (en) | 2013-09-05 | 2017-05-31 | Barclays Bank Plc | Biometric verification using predicted signatures |
US9208779B2 (en) | 2013-09-06 | 2015-12-08 | Google Inc. | Mixture of n-gram language models |
US9460704B2 (en) | 2013-09-06 | 2016-10-04 | Google Inc. | Deep networks for unit selection speech synthesis |
US9898642B2 (en) | 2013-09-09 | 2018-02-20 | Apple Inc. | Device, method, and graphical user interface for manipulating user interfaces based on fingerprint sensor inputs |
US20150074524A1 (en) | 2013-09-10 | 2015-03-12 | Lenovo (Singapore) Pte. Ltd. | Management of virtual assistant action items |
US9485708B2 (en) | 2013-09-10 | 2016-11-01 | Qualcomm Incorporated | Systems and methods for concurrent service discovery and minimum spanning tree formation for service delivery |
CN104700832B (en) | 2013-12-09 | 2018-05-25 | 联发科技股份有限公司 | Voiced keyword detecting system and method |
US9755605B1 (en) | 2013-09-19 | 2017-09-05 | Amazon Technologies, Inc. | Volume control |
CN105793923A (en) | 2013-09-20 | 2016-07-20 | 亚马逊技术股份有限公司 | Local and remote speech processing |
CN104463552B (en) | 2013-09-22 | 2018-10-02 | 中国电信股份有限公司 | Calendar reminding generation method and device |
US20150088511A1 (en) | 2013-09-24 | 2015-03-26 | Verizon Patent And Licensing Inc. | Named-entity based speech recognition |
US9418650B2 (en) | 2013-09-25 | 2016-08-16 | Verizon Patent And Licensing Inc. | Training speech recognition using captions |
US10134395B2 (en) | 2013-09-25 | 2018-11-20 | Amazon Technologies, Inc. | In-call virtual assistants |
CN104516522B (en) | 2013-09-29 | 2018-05-01 | 北京三星通信技术研究有限公司 | The method and apparatus of nine grids input through keyboard |
US20150095278A1 (en) | 2013-09-30 | 2015-04-02 | Manyworlds, Inc. | Adaptive Probabilistic Semantic System and Method |
US20150095031A1 (en) | 2013-09-30 | 2015-04-02 | At&T Intellectual Property I, L.P. | System and method for crowdsourcing of word pronunciation verification |
US20150100537A1 (en) | 2013-10-03 | 2015-04-09 | Microsoft Corporation | Emoji for Text Predictions |
US20150100983A1 (en) | 2013-10-06 | 2015-04-09 | Yang Pan | Personal Mobile Device as Ad hoc Set-Top Box for Television |
US9436918B2 (en) | 2013-10-07 | 2016-09-06 | Microsoft Technology Licensing, Llc | Smart selection of text spans |
KR101480474B1 (en) * | 2013-10-08 | 2015-01-09 | 엘지전자 주식회사 | Audio playing apparatus and systme habving the samde |
US20150100313A1 (en) | 2013-10-09 | 2015-04-09 | Verizon Patent And Licensing, Inc. | Personification of computing devices for remote access |
US8996639B1 (en) | 2013-10-15 | 2015-03-31 | Google Inc. | Predictive responses to incoming communications |
US9063640B2 (en) * | 2013-10-17 | 2015-06-23 | Spotify Ab | System and method for switching between media items in a plurality of sequences of media items |
US20150120723A1 (en) | 2013-10-24 | 2015-04-30 | Xerox Corporation | Methods and systems for processing speech queries |
US20150120296A1 (en) | 2013-10-29 | 2015-04-30 | At&T Intellectual Property I, L.P. | System and method for selecting network-based versus embedded speech processing |
US10055681B2 (en) | 2013-10-31 | 2018-08-21 | Verint Americas Inc. | Mapping actions and objects to tasks |
US9942396B2 (en) | 2013-11-01 | 2018-04-10 | Adobe Systems Incorporated | Document distribution and interaction |
US9183830B2 (en) | 2013-11-01 | 2015-11-10 | Google Inc. | Method and system for non-parametric voice conversion |
US10019985B2 (en) | 2013-11-04 | 2018-07-10 | Google Llc | Asynchronous optimization for sequence training of neural networks |
US10088973B2 (en) | 2013-11-08 | 2018-10-02 | Google Llc | Event scheduling presentation in a graphical user interface environment |
JP6493866B2 (en) | 2013-11-12 | 2019-04-03 | インターナショナル・ビジネス・マシーンズ・コーポレーションInternational Business Machines Corporation | Information processing apparatus, information processing method, and program |
GB2520266A (en) | 2013-11-13 | 2015-05-20 | Ibm | Cursor-Based Character input interface |
US10430024B2 (en) | 2013-11-13 | 2019-10-01 | Microsoft Technology Licensing, Llc | Media item selection using user-specific grammar |
US9361084B1 (en) | 2013-11-14 | 2016-06-07 | Google Inc. | Methods and systems for installing and executing applications |
US10110932B2 (en) | 2013-11-18 | 2018-10-23 | Cable Television Laboratories, Inc. | Session administration |
US9443522B2 (en) | 2013-11-18 | 2016-09-13 | Beijing Lenovo Software Ltd. | Voice recognition method, voice controlling method, information processing method, and electronic apparatus |
US9898554B2 (en) | 2013-11-18 | 2018-02-20 | Google Inc. | Implicit question query identification |
US10162813B2 (en) | 2013-11-21 | 2018-12-25 | Microsoft Technology Licensing, Llc | Dialogue evaluation via multiple hypothesis ranking |
US10079013B2 (en) | 2013-11-27 | 2018-09-18 | Sri International | Sharing intents to provide virtual assistance in a multi-person dialog |
US9451434B2 (en) | 2013-11-27 | 2016-09-20 | At&T Intellectual Property I, L.P. | Direct interaction between a user and a communication network |
US20150149354A1 (en) | 2013-11-27 | 2015-05-28 | Bank Of America Corporation | Real-Time Data Recognition and User Interface Field Updating During Voice Entry |
US9698999B2 (en) | 2013-12-02 | 2017-07-04 | Amazon Technologies, Inc. | Natural language control of secondary device |
US8719039B1 (en) | 2013-12-05 | 2014-05-06 | Google Inc. | Promoting voice actions to hotwords |
WO2015085237A1 (en) | 2013-12-06 | 2015-06-11 | Adt Us Holdings, Inc. | Voice activated application for mobile devices |
US9215510B2 (en) | 2013-12-06 | 2015-12-15 | Rovi Guides, Inc. | Systems and methods for automatically tagging a media asset based on verbal input and playback adjustments |
US10296160B2 (en) | 2013-12-06 | 2019-05-21 | Apple Inc. | Method for extracting salient dialog usage from live data |
US20150162001A1 (en) | 2013-12-10 | 2015-06-11 | Honeywell International Inc. | System and method for textually and graphically presenting air traffic control voice information |
US20150160855A1 (en) | 2013-12-10 | 2015-06-11 | Google Inc. | Multiple character input with a single selection |
US9208153B1 (en) | 2013-12-13 | 2015-12-08 | Symantec Corporation | Filtering relevant event notifications in a file sharing and collaboration environment |
WO2015094169A1 (en) | 2013-12-16 | 2015-06-25 | Nuance Communications, Inc. | Systems and methods for providing a virtual assistant |
US10534623B2 (en) | 2013-12-16 | 2020-01-14 | Nuance Communications, Inc. | Systems and methods for providing a virtual assistant |
US9479931B2 (en) | 2013-12-16 | 2016-10-25 | Nuance Communications, Inc. | Systems and methods for providing a virtual assistant |
US9571645B2 (en) | 2013-12-16 | 2017-02-14 | Nuance Communications, Inc. | Systems and methods for providing a virtual assistant |
US9804820B2 (en) | 2013-12-16 | 2017-10-31 | Nuance Communications, Inc. | Systems and methods for providing a virtual assistant |
WO2015092943A1 (en) | 2013-12-17 | 2015-06-25 | Sony Corporation | Electronic devices and methods for compensating for environmental noise in text-to-speech applications |
GB2523984B (en) | 2013-12-18 | 2017-07-26 | Cirrus Logic Int Semiconductor Ltd | Processing received speech data |
US9741343B1 (en) | 2013-12-19 | 2017-08-22 | Amazon Technologies, Inc. | Voice interaction application selection |
US10565268B2 (en) | 2013-12-19 | 2020-02-18 | Adobe Inc. | Interactive communication augmented with contextual information |
KR20150072231A (en) * | 2013-12-19 | 2015-06-29 | 한국전자통신연구원 | Apparatus and method for providing muti angle view service |
EP3084760A4 (en) | 2013-12-20 | 2017-08-16 | Intel Corporation | Transition from low power always listening mode to high power speech recognition mode |
KR102179506B1 (en) | 2013-12-23 | 2020-11-17 | 삼성전자 주식회사 | Electronic apparatus and control method thereof |
JP6121896B2 (en) | 2013-12-27 | 2017-04-26 | 株式会社ソニー・インタラクティブエンタテインメント | Information processing apparatus and information processing system |
WO2015100172A1 (en) | 2013-12-27 | 2015-07-02 | Kopin Corporation | Text editing with gesture control and natural speech |
KR102092164B1 (en) | 2013-12-27 | 2020-03-23 | 삼성전자주식회사 | Display device, server device, display system comprising them and methods thereof |
US9460735B2 (en) | 2013-12-28 | 2016-10-04 | Intel Corporation | Intelligent ancillary electronic device |
US10078489B2 (en) | 2013-12-30 | 2018-09-18 | Microsoft Technology Licensing, Llc | Voice interface to a social networking service |
US9390726B1 (en) | 2013-12-30 | 2016-07-12 | Google Inc. | Supplementing speech commands with gestures |
US9424241B2 (en) | 2013-12-31 | 2016-08-23 | Barnes & Noble College Booksellers, Llc | Annotation mode including multiple note types for paginated digital content |
US9152307B2 (en) | 2013-12-31 | 2015-10-06 | Google Inc. | Systems and methods for simultaneously displaying clustered, in-line electronic messages in one display |
US9823811B2 (en) | 2013-12-31 | 2017-11-21 | Next It Corporation | Virtual assistant team identification |
US9274673B2 (en) | 2013-12-31 | 2016-03-01 | Google Inc. | Methods, systems, and media for rewinding media content based on detected audio events |
US9742836B2 (en) | 2014-01-03 | 2017-08-22 | Yahoo Holdings, Inc. | Systems and methods for content delivery |
US20150193379A1 (en) | 2014-01-06 | 2015-07-09 | Apple Inc. | System and method for cognizant time-based reminders |
US8938394B1 (en) | 2014-01-09 | 2015-01-20 | Google Inc. | Audio triggers based on context |
US9443516B2 (en) | 2014-01-09 | 2016-09-13 | Honeywell International Inc. | Far-field speech recognition systems and methods |
US9924215B2 (en) | 2014-01-09 | 2018-03-20 | Hsni, Llc | Digital media content management system and method |
US20150201077A1 (en) | 2014-01-12 | 2015-07-16 | Genesys Telecommunications Laboratories, Inc. | Computing suggested actions in caller agent phone calls by using real-time speech analytics and real-time desktop analytics |
US9514748B2 (en) | 2014-01-15 | 2016-12-06 | Microsoft Technology Licensing, Llc | Digital personal assistant interaction with impersonations and rich multimedia in responses |
US20150199965A1 (en) | 2014-01-16 | 2015-07-16 | CloudCar Inc. | System and method for recognition and automatic correction of voice commands |
US8868409B1 (en) | 2014-01-16 | 2014-10-21 | Google Inc. | Evaluating transcriptions with a semantic parser |
US9336300B2 (en) | 2014-01-17 | 2016-05-10 | Facebook, Inc. | Client-side search templates for online social networks |
CN103744761B (en) | 2014-01-22 | 2017-02-08 | 广东欧珀移动通信有限公司 | Method and system for controlling multiple mobile terminals to automatically execute tasks |
CN105900042B (en) | 2014-01-22 | 2019-06-28 | 索尼公司 | Redirect the method and apparatus of audio input and output |
WO2015112137A1 (en) | 2014-01-22 | 2015-07-30 | Pearl Capital Developments Llc | Coordinated hand-off of audio data transmission |
CN103760984A (en) | 2014-01-24 | 2014-04-30 | 成都万先自动化科技有限责任公司 | Man-machine conversation system |
US11386886B2 (en) | 2014-01-28 | 2022-07-12 | Lenovo (Singapore) Pte. Ltd. | Adjusting speech recognition using contextual information |
US9858039B2 (en) | 2014-01-28 | 2018-01-02 | Oracle International Corporation | Voice recognition of commands extracted from user interface screen devices |
US10019060B2 (en) | 2014-01-30 | 2018-07-10 | Duane Matthew Cash | Mind-controlled virtual assistant on a smartphone device |
US20160173960A1 (en) | 2014-01-31 | 2016-06-16 | EyeGroove, Inc. | Methods and systems for generating audiovisual media items |
WO2015116151A1 (en) | 2014-01-31 | 2015-08-06 | Hewlett-Packard Development Company, L.P. | Voice input command |
US9292488B2 (en) | 2014-02-01 | 2016-03-22 | Soundhound, Inc. | Method for embedding voice mail in a spoken utterance using a natural language processing computer system |
US10028008B2 (en) * | 2014-02-04 | 2018-07-17 | Google Llc | Persistent media player |
JP6188831B2 (en) | 2014-02-06 | 2017-08-30 | 三菱電機株式会社 | Voice search apparatus and voice search method |
US20150228281A1 (en) | 2014-02-07 | 2015-08-13 | First Principles,Inc. | Device, system, and method for active listening |
US10083205B2 (en) | 2014-02-12 | 2018-09-25 | Samsung Electronics Co., Ltd. | Query cards |
US9037967B1 (en) | 2014-02-18 | 2015-05-19 | King Fahd University Of Petroleum And Minerals | Arabic spell checking technique |
US9589562B2 (en) | 2014-02-21 | 2017-03-07 | Microsoft Technology Licensing, Llc | Pronunciation learning through correction logs |
US10691292B2 (en) | 2014-02-24 | 2020-06-23 | Microsoft Technology Licensing, Llc | Unified presentation of contextually connected information to improve user efficiency and interaction performance |
US9495959B2 (en) | 2014-02-27 | 2016-11-15 | Ford Global Technologies, Llc | Disambiguation of dynamic commands |
US20150248651A1 (en) * | 2014-02-28 | 2015-09-03 | Christine E. Akutagawa | Social networking event planning |
US9412363B2 (en) | 2014-03-03 | 2016-08-09 | Microsoft Technology Licensing, Llc | Model based approach for on-screen item selection and disambiguation |
US20150256873A1 (en) | 2014-03-04 | 2015-09-10 | Microsoft Technology Licensing, Llc | Relayed voice control of devices |
US9582246B2 (en) | 2014-03-04 | 2017-02-28 | Microsoft Technology Licensing, Llc | Voice-command suggestions based on computer context |
US9489171B2 (en) * | 2014-03-04 | 2016-11-08 | Microsoft Technology Licensing, Llc | Voice-command suggestions based on user identity |
US9286910B1 (en) | 2014-03-13 | 2016-03-15 | Amazon Technologies, Inc. | System for resolving ambiguous queries based on user context |
US9405377B2 (en) * | 2014-03-15 | 2016-08-02 | Microsoft Technology Licensing, Llc | Trainable sensor-based gesture recognition |
US10102274B2 (en) | 2014-03-17 | 2018-10-16 | NLPCore LLC | Corpus search systems and methods |
US9430186B2 (en) | 2014-03-17 | 2016-08-30 | Google Inc | Visual indication of a recognized voice-initiated action |
US9336306B2 (en) | 2014-03-21 | 2016-05-10 | International Business Machines Corporation | Automatic evaluation and improvement of ontologies for natural language processing tasks |
US9734817B1 (en) | 2014-03-21 | 2017-08-15 | Amazon Technologies, Inc. | Text-to-speech task scheduling |
US9710546B2 (en) | 2014-03-28 | 2017-07-18 | Microsoft Technology Licensing, Llc | Explicit signals personalized search |
IN2014DE00899A (en) | 2014-03-28 | 2015-10-02 | Samsung Electronics Co Ltd | |
JPWO2015151157A1 (en) | 2014-03-31 | 2017-04-13 | 三菱電機株式会社 | Intent understanding apparatus and method |
US9196243B2 (en) | 2014-03-31 | 2015-11-24 | International Business Machines Corporation | Method and system for efficient spoken term detection using confusion networks |
US9286892B2 (en) | 2014-04-01 | 2016-03-15 | Google Inc. | Language modeling in speech recognition |
US20150278370A1 (en) | 2014-04-01 | 2015-10-01 | Microsoft Corporation | Task completion for natural language input |
KR101873671B1 (en) | 2014-04-02 | 2018-07-02 | 소니 주식회사 | Power efficient proximity detection |
US20150286627A1 (en) | 2014-04-03 | 2015-10-08 | Adobe Systems Incorporated | Contextual sentiment text analysis |
KR102249086B1 (en) | 2014-04-04 | 2021-05-10 | 삼성전자주식회사 | Electronic Apparatus and Method for Supporting of Recording |
KR20150115555A (en) | 2014-04-04 | 2015-10-14 | 삼성전자주식회사 | Electronic device And Method for providing information thereof |
US9519644B2 (en) | 2014-04-04 | 2016-12-13 | Facebook, Inc. | Methods and devices for generating media items |
US9383827B1 (en) | 2014-04-07 | 2016-07-05 | Google Inc. | Multi-modal command display |
JP6282516B2 (en) | 2014-04-08 | 2018-02-21 | パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカPanasonic Intellectual Property Corporation of America | Multi-device voice operation system, voice operation method, and program |
US9888452B2 (en) | 2014-04-10 | 2018-02-06 | Twin Harbor Labs Llc | Methods and apparatus notifying a user of the operating condition of a household appliance |
US20150294516A1 (en) | 2014-04-10 | 2015-10-15 | Kuo-Ching Chiang | Electronic device with security module |
US20170178664A1 (en) | 2014-04-11 | 2017-06-22 | Analog Devices, Inc. | Apparatus, systems and methods for providing cloud based blind source separation services |
CN108551675B (en) | 2014-04-14 | 2022-04-15 | 创新先进技术有限公司 | Application client, server and corresponding Portal authentication method |
US9582499B2 (en) | 2014-04-14 | 2017-02-28 | Xerox Corporation | Retrieval of domain relevant phrase tables |
US20150294086A1 (en) | 2014-04-14 | 2015-10-15 | Elwha Llc | Devices, systems, and methods for automated enhanced care rooms |
US20150302856A1 (en) | 2014-04-17 | 2015-10-22 | Qualcomm Incorporated | Method and apparatus for performing function by speech input |
US10770075B2 (en) | 2014-04-21 | 2020-09-08 | Qualcomm Incorporated | Method and apparatus for activating application by speech input |
US9607613B2 (en) | 2014-04-23 | 2017-03-28 | Google Inc. | Speech endpointing based on word comparisons |
US20150310862A1 (en) | 2014-04-24 | 2015-10-29 | Microsoft Corporation | Deep learning for semantic parsing including semantic utterance classification |
US10845982B2 (en) | 2014-04-28 | 2020-11-24 | Facebook, Inc. | Providing intelligent transcriptions of sound messages in a messaging application |
US9520127B2 (en) | 2014-04-29 | 2016-12-13 | Microsoft Technology Licensing, Llc | Shared hidden layer combination for speech recognition systems |
US9600600B2 (en) | 2014-04-30 | 2017-03-21 | Excalibur Ip, Llc | Method and system for evaluating query suggestions quality |
KR102248474B1 (en) | 2014-04-30 | 2021-05-07 | 삼성전자 주식회사 | Voice command providing method and apparatus |
US9501163B2 (en) | 2014-05-06 | 2016-11-22 | Symbol Technologies, Llc | Apparatus and method for activating a trigger mechanism |
KR102282487B1 (en) | 2014-05-08 | 2021-07-26 | 삼성전자주식회사 | Apparatus and method for executing application |
US9620105B2 (en) | 2014-05-15 | 2017-04-11 | Apple Inc. | Analyzing audio input for efficient speech and music recognition |
US9459889B2 (en) | 2014-05-19 | 2016-10-04 | Qualcomm Incorporated | Systems and methods for context-aware application control |
KR102216048B1 (en) | 2014-05-20 | 2021-02-15 | 삼성전자주식회사 | Apparatus and method for recognizing voice commend |
US10726831B2 (en) | 2014-05-20 | 2020-07-28 | Amazon Technologies, Inc. | Context interpretation in natural language processing using previous dialog acts |
KR102223278B1 (en) | 2014-05-22 | 2021-03-05 | 엘지전자 주식회사 | Glass type terminal and control method thereof |
US9990433B2 (en) | 2014-05-23 | 2018-06-05 | Samsung Electronics Co., Ltd. | Method for searching and device thereof |
US10592095B2 (en) | 2014-05-23 | 2020-03-17 | Apple Inc. | Instantaneous speaking of content on touch devices |
US9502031B2 (en) | 2014-05-27 | 2016-11-22 | Apple Inc. | Method for supporting dynamic grammars in WFST-based ASR |
US9437189B2 (en) | 2014-05-29 | 2016-09-06 | Google Inc. | Generating language models |
US9519634B2 (en) | 2014-05-30 | 2016-12-13 | Educational Testing Service | Systems and methods for determining lexical associations among words in a corpus |
TWI520007B (en) | 2014-05-30 | 2016-02-01 | 由田新技股份有限公司 | Eye-controlled password input apparatus, method, computer readable medium, and computer program product thereof |
US20150350118A1 (en) | 2014-05-30 | 2015-12-03 | Apple Inc. | Canned answers in messages |
US10033818B2 (en) | 2014-05-30 | 2018-07-24 | Apple Inc. | Using listen ranges to deliver content to electronic devices from local caching servers |
US10078631B2 (en) | 2014-05-30 | 2018-09-18 | Apple Inc. | Entropy-guided text prediction using combined word and character n-gram language models |
US9842101B2 (en) | 2014-05-30 | 2017-12-12 | Apple Inc. | Predictive conversion of language input |
US9760559B2 (en) | 2014-05-30 | 2017-09-12 | Apple Inc. | Predictive text input |
US9633004B2 (en) | 2014-05-30 | 2017-04-25 | Apple Inc. | Better resolution when referencing to concepts |
US10579212B2 (en) | 2014-05-30 | 2020-03-03 | Apple Inc. | Structured suggestions |
WO2015184387A1 (en) | 2014-05-30 | 2015-12-03 | Apple Inc. | Accessory management system using environment model |
US10170123B2 (en) | 2014-05-30 | 2019-01-01 | Apple Inc. | Intelligent assistant for home automation |
US9380123B2 (en) | 2014-05-30 | 2016-06-28 | Apple Inc. | Activity continuation between electronic devices |
US9966065B2 (en) | 2014-05-30 | 2018-05-08 | Apple Inc. | Multi-command single utterance input method |
US9715875B2 (en) | 2014-05-30 | 2017-07-25 | Apple Inc. | Reducing the need for manual start/end-pointing and trigger phrases |
US9430463B2 (en) | 2014-05-30 | 2016-08-30 | Apple Inc. | Exemplar-based natural language processing |
US9654536B2 (en) | 2014-06-04 | 2017-05-16 | Sonos, Inc. | Cloud queue playback policy |
US8995972B1 (en) | 2014-06-05 | 2015-03-31 | Grandios Technologies, Llc | Automatic personal assistance between users devices |
JP6307356B2 (en) | 2014-06-06 | 2018-04-04 | 株式会社デンソー | Driving context information generator |
US10432742B2 (en) | 2014-06-06 | 2019-10-01 | Google Llc | Proactive environment-based chat information system |
US10325205B2 (en) | 2014-06-09 | 2019-06-18 | Cognitive Scale, Inc. | Cognitive information processing system environment |
EP3690610B1 (en) | 2014-06-11 | 2022-10-12 | Honor Device Co., Ltd. | Method for quickly starting application service, and terminal |
CN104090652B (en) | 2014-06-13 | 2017-07-21 | 北京搜狗科技发展有限公司 | A kind of pronunciation inputting method and device |
US20150364140A1 (en) | 2014-06-13 | 2015-12-17 | Sony Corporation | Portable Electronic Equipment and Method of Operating a User Interface |
US10127901B2 (en) | 2014-06-13 | 2018-11-13 | Microsoft Technology Licensing, Llc | Hyper-structure recurrent neural networks for text-to-speech |
US9390706B2 (en) | 2014-06-19 | 2016-07-12 | Mattersight Corporation | Personality-based intelligent personal assistant system and methods |
US9462112B2 (en) | 2014-06-19 | 2016-10-04 | Microsoft Technology Licensing, Llc | Use of a digital assistant in communications |
US10186282B2 (en) | 2014-06-19 | 2019-01-22 | Apple Inc. | Robust end-pointing of speech signals using speaker recognition |
US20150371529A1 (en) | 2014-06-24 | 2015-12-24 | Bose Corporation | Audio Systems and Related Methods and Devices |
US9384738B2 (en) | 2014-06-24 | 2016-07-05 | Google Inc. | Dynamic threshold for speaker verification |
US9632748B2 (en) | 2014-06-24 | 2017-04-25 | Google Inc. | Device designation for audio input monitoring |
US9807559B2 (en) | 2014-06-25 | 2017-10-31 | Microsoft Technology Licensing, Llc | Leveraging user signals for improved interactions with digital personal assistant |
US10402453B2 (en) | 2014-06-27 | 2019-09-03 | Nuance Communications, Inc. | Utilizing large-scale knowledge graphs to support inference at scale and explanation generation |
US20150381923A1 (en) * | 2014-06-27 | 2015-12-31 | United Video Properties, Inc. | Methods and systems for adjusting a play length of a media asset based user actions |
US20150379118A1 (en) * | 2014-06-27 | 2015-12-31 | United Video Properties, Inc. | Methods and systems for generating playlists based on activities being performed by a user |
US10659851B2 (en) | 2014-06-30 | 2020-05-19 | Apple Inc. | Real-time digital assistant knowledge updates |
KR102261552B1 (en) | 2014-06-30 | 2021-06-07 | 삼성전자주식회사 | Providing Method For Voice Command and Electronic Device supporting the same |
US9338493B2 (en) | 2014-06-30 | 2016-05-10 | Apple Inc. | Intelligent automated assistant for TV user interactions |
WO2016004396A1 (en) | 2014-07-02 | 2016-01-07 | Christopher Decharms | Technologies for brain exercise training |
US20160012038A1 (en) | 2014-07-10 | 2016-01-14 | International Business Machines Corporation | Semantic typing with n-gram analysis |
US10321204B2 (en) | 2014-07-11 | 2019-06-11 | Lenovo (Singapore) Pte. Ltd. | Intelligent closed captioning |
US9665248B2 (en) * | 2014-07-15 | 2017-05-30 | Google Inc. | Adaptive background playback behavior |
KR20160009344A (en) | 2014-07-16 | 2016-01-26 | 삼성전자주식회사 | Method and apparatus for recognizing whispered voice |
US9257120B1 (en) | 2014-07-18 | 2016-02-09 | Google Inc. | Speaker verification using co-location information |
JP6434144B2 (en) | 2014-07-18 | 2018-12-05 | アップル インコーポレイテッドApple Inc. | Raise gesture detection on devices |
US20160028666A1 (en) | 2014-07-24 | 2016-01-28 | Framy Inc. | System and method for instant messaging |
US9301256B2 (en) | 2014-07-24 | 2016-03-29 | Verizon Patent And Licensing Inc. | Low battery indication for callers to mobile device |
US20160086116A1 (en) | 2014-07-27 | 2016-03-24 | Supriya Rao | Method and system of an automatically managed calendar and contextual task list |
WO2016017997A1 (en) | 2014-07-31 | 2016-02-04 | Samsung Electronics Co., Ltd. | Wearable glasses and method of providing content using the same |
US20160034811A1 (en) | 2014-07-31 | 2016-02-04 | Apple Inc. | Efficient generation of complementary acoustic models for performing automatic speech recognition system combination |
US9377871B2 (en) | 2014-08-01 | 2016-06-28 | Nuance Communications, Inc. | System and methods for determining keyboard input in the presence of multiple contact points |
US9874997B2 (en) * | 2014-08-08 | 2018-01-23 | Sonos, Inc. | Social playback queues |
US9548066B2 (en) | 2014-08-11 | 2017-01-17 | Amazon Technologies, Inc. | Voice application architecture |
US9767794B2 (en) | 2014-08-11 | 2017-09-19 | Nuance Communications, Inc. | Dialog flow management in hierarchical task dialogs |
US9361442B2 (en) | 2014-08-12 | 2016-06-07 | International Business Machines Corporation | Triggering actions on a user device based on biometrics of nearby individuals |
US9838999B2 (en) | 2014-08-14 | 2017-12-05 | Blackberry Limited | Portable electronic device and method of controlling notifications |
JP6044604B2 (en) | 2014-08-18 | 2016-12-14 | カシオ計算機株式会社 | Terminal device and program |
US10345767B2 (en) | 2014-08-19 | 2019-07-09 | Samsung Electronics Co., Ltd. | Apparatus and method for gamification of sensor data interpretation in smart home |
KR20160023089A (en) | 2014-08-21 | 2016-03-03 | 엘지전자 주식회사 | Digital device and method for controlling the same |
US20160055240A1 (en) | 2014-08-22 | 2016-02-25 | Microsoft Corporation | Orphaned utterance detection system and method |
DE202015005999U1 (en) | 2014-08-26 | 2015-11-26 | Apple Inc. | User interface for restricting messages and alarms |
US10446141B2 (en) | 2014-08-28 | 2019-10-15 | Apple Inc. | Automatic speech recognition based on user feedback |
US9990610B2 (en) | 2014-08-29 | 2018-06-05 | Google Llc | Systems and methods for providing suggested reminders |
CN105471705B (en) | 2014-09-03 | 2021-03-23 | 腾讯科技(深圳)有限公司 | Intelligent control method, equipment and system based on instant messaging |
US9959863B2 (en) | 2014-09-08 | 2018-05-01 | Qualcomm Incorporated | Keyword detection using speaker-independent keyword models for user-designated keywords |
US10019990B2 (en) | 2014-09-09 | 2018-07-10 | Microsoft Technology Licensing, Llc | Variable-component deep neural network for robust speech recognition |
US10204622B2 (en) | 2015-09-10 | 2019-02-12 | Crestron Electronics, Inc. | Acoustic sensory network |
US9818400B2 (en) | 2014-09-11 | 2017-11-14 | Apple Inc. | Method and apparatus for discovering trending terms in speech requests |
US10789041B2 (en) | 2014-09-12 | 2020-09-29 | Apple Inc. | Dynamic thresholds for always listening speech trigger |
CN105490890A (en) | 2014-09-16 | 2016-04-13 | 中兴通讯股份有限公司 | Intelligent household terminal and control method therefor |
US9778736B2 (en) * | 2014-09-22 | 2017-10-03 | Rovi Guides, Inc. | Methods and systems for calibrating user devices |
US9508028B2 (en) | 2014-09-24 | 2016-11-29 | Nuance Communications, Inc. | Converting text strings into number strings, such as via a touchscreen input |
US10317992B2 (en) | 2014-09-25 | 2019-06-11 | Microsoft Technology Licensing, Llc | Eye gaze for spoken language understanding in multi-modal conversational interactions |
US20160094889A1 (en) * | 2014-09-29 | 2016-03-31 | Rovi Guides, Inc. | Systems and methods for determining whether to merge search queries based on contextual information |
US9646609B2 (en) | 2014-09-30 | 2017-05-09 | Apple Inc. | Caching apparatus for serving phonetic pronunciations |
US9378740B1 (en) | 2014-09-30 | 2016-06-28 | Amazon Technologies, Inc. | Command suggestions during automatic speech recognition |
US9646634B2 (en) | 2014-09-30 | 2017-05-09 | Google Inc. | Low-rank hidden input layer for speech recognition neural network |
US10127911B2 (en) | 2014-09-30 | 2018-11-13 | Apple Inc. | Speaker identification and unsupervised speaker adaptation techniques |
US9668121B2 (en) | 2014-09-30 | 2017-05-30 | Apple Inc. | Social reminders |
US9578156B2 (en) | 2014-09-30 | 2017-02-21 | Samsung Electronics Co., Ltd. | Method and apparatus for operating an electronic device |
US9886432B2 (en) | 2014-09-30 | 2018-02-06 | Apple Inc. | Parsimonious handling of word inflection via categorical stem + suffix N-gram language models |
US10074360B2 (en) | 2014-09-30 | 2018-09-11 | Apple Inc. | Providing an indication of the suitability of speech recognition |
US9830321B2 (en) | 2014-09-30 | 2017-11-28 | Rovi Guides, Inc. | Systems and methods for searching for a media asset |
JP6671379B2 (en) | 2014-10-01 | 2020-03-25 | エクスブレイン・インコーポレーテッド | Voice and connectivity platforms |
US9812128B2 (en) | 2014-10-09 | 2017-11-07 | Google Inc. | Device leadership negotiation among voice interface devices |
US9318107B1 (en) | 2014-10-09 | 2016-04-19 | Google Inc. | Hotword detection on multiple devices |
US9741344B2 (en) | 2014-10-20 | 2017-08-22 | Vocalzoom Systems Ltd. | System and method for operating devices using voice commands |
US20160117386A1 (en) | 2014-10-22 | 2016-04-28 | International Business Machines Corporation | Discovering terms using statistical corpus analysis |
US9576575B2 (en) | 2014-10-27 | 2017-02-21 | Toyota Motor Engineering & Manufacturing North America, Inc. | Providing voice recognition shortcuts based on user verbal input |
CN104460593B (en) | 2014-10-29 | 2017-10-10 | 小米科技有限责任公司 | mode switching method and device |
US9880714B2 (en) | 2014-10-30 | 2018-01-30 | Ebay Inc. | Dynamic loading of contextual ontologies for predictive touch screen typing |
CN105574067B (en) | 2014-10-31 | 2020-01-21 | 株式会社东芝 | Item recommendation device and item recommendation method |
US9646611B2 (en) | 2014-11-06 | 2017-05-09 | Microsoft Technology Licensing, Llc | Context-based actions |
US9678946B2 (en) | 2014-11-10 | 2017-06-13 | Oracle International Corporation | Automatic generation of N-grams and concept relations from linguistic input data |
GB2532075A (en) | 2014-11-10 | 2016-05-11 | Lego As | System and method for toy recognition and detection based on convolutional neural networks |
US10572589B2 (en) | 2014-11-10 | 2020-02-25 | International Business Machines Corporation | Cognitive matching of narrative data |
US9542927B2 (en) | 2014-11-13 | 2017-01-10 | Google Inc. | Method and system for building text-to-speech voice from diverse recordings |
US20160139662A1 (en) | 2014-11-14 | 2016-05-19 | Sachin Dabhade | Controlling a visual device based on a proximity between a user and the visual device |
US10116748B2 (en) * | 2014-11-20 | 2018-10-30 | Microsoft Technology Licensing, Llc | Vehicle-based multi-modal interface |
US9258604B1 (en) | 2014-11-24 | 2016-02-09 | Facebook, Inc. | Commercial detection based on audio fingerprinting |
US9886430B2 (en) | 2014-11-25 | 2018-02-06 | Microsoft Technology Licensing, Llc | Entity based content selection |
US10614799B2 (en) | 2014-11-26 | 2020-04-07 | Voicebox Technologies Corporation | System and method of providing intent predictions for an utterance prior to a system detection of an end of the utterance |
US10192549B2 (en) | 2014-11-28 | 2019-01-29 | Microsoft Technology Licensing, Llc | Extending digital personal assistant action providers |
US9812126B2 (en) | 2014-11-28 | 2017-11-07 | Microsoft Technology Licensing, Llc | Device arbitration for listening devices |
EP3228084A4 (en) | 2014-12-01 | 2018-04-25 | Inscape Data, Inc. | System and method for continuous media segment identification |
US9466297B2 (en) | 2014-12-09 | 2016-10-11 | Microsoft Technology Licensing, Llc | Communication system |
US9241073B1 (en) | 2014-12-09 | 2016-01-19 | Ringcentral, Inc. | Systems and methods for managing an event scheduling request in a telephony system |
US9711141B2 (en) | 2014-12-09 | 2017-07-18 | Apple Inc. | Disambiguating heteronyms in speech synthesis |
US10127214B2 (en) | 2014-12-09 | 2018-11-13 | Sansa Al Inc. | Methods for generating natural language processing systems |
US20160170966A1 (en) | 2014-12-10 | 2016-06-16 | Brian Kolo | Methods and systems for automated language identification |
CN111399801B (en) | 2014-12-11 | 2023-07-25 | 微软技术许可有限责任公司 | Virtual assistant system capable of actionable messaging |
US9912758B2 (en) | 2014-12-16 | 2018-03-06 | Yahoo Holdings, Inc. | Continuing an application session on a different device |
US9904673B2 (en) | 2014-12-17 | 2018-02-27 | International Business Machines Corporation | Conversation advisor |
US9911415B2 (en) | 2014-12-19 | 2018-03-06 | Lenovo (Singapore) Pte. Ltd. | Executing a voice command during voice input |
US9552816B2 (en) | 2014-12-19 | 2017-01-24 | Amazon Technologies, Inc. | Application focus in speech-based systems |
KR20160076201A (en) | 2014-12-22 | 2016-06-30 | 엘지전자 주식회사 | Mobile terminal and method for controlling the same |
US9811312B2 (en) | 2014-12-22 | 2017-11-07 | Intel Corporation | Connected device voice command support |
JP6504808B2 (en) | 2014-12-22 | 2019-04-24 | キヤノン株式会社 | Imaging device, setting method of voice command function, computer program, and storage medium |
US9837081B2 (en) | 2014-12-30 | 2017-12-05 | Microsoft Technology Licensing, Llc | Discovering capabilities of third-party voice-enabled resources |
US9959129B2 (en) | 2015-01-09 | 2018-05-01 | Microsoft Technology Licensing, Llc | Headless task completion within digital personal assistants |
KR102305584B1 (en) | 2015-01-19 | 2021-09-27 | 삼성전자주식회사 | Method and apparatus for training language model, method and apparatus for recognizing language |
US9367541B1 (en) | 2015-01-20 | 2016-06-14 | Xerox Corporation | Terminological adaptation of statistical machine translation system through automatic generation of phrasal contexts for bilingual terms |
US9424412B1 (en) | 2015-02-02 | 2016-08-23 | Bank Of America Corporation | Authenticating customers using biometrics |
US20160225372A1 (en) | 2015-02-03 | 2016-08-04 | Samsung Electronics Company, Ltd. | Smart home connected device contextual learning using audio commands |
US9613022B2 (en) | 2015-02-04 | 2017-04-04 | Lenovo (Singapore) Pte. Ltd. | Context based customization of word assistance functions |
KR101678087B1 (en) | 2015-02-16 | 2016-11-23 | 현대자동차주식회사 | Vehicle and method of controlling the same |
KR20160101826A (en) | 2015-02-17 | 2016-08-26 | 삼성전자주식회사 | Multi-Users Based Device |
JP2016151928A (en) | 2015-02-18 | 2016-08-22 | ソニー株式会社 | Information processing device, information processing method, and program |
EP3259688A4 (en) | 2015-02-19 | 2018-12-12 | Digital Reasoning Systems, Inc. | Systems and methods for neural language modeling |
US9928232B2 (en) | 2015-02-27 | 2018-03-27 | Microsoft Technology Licensing, Llc | Topically aware word suggestions |
US9865280B2 (en) | 2015-03-06 | 2018-01-09 | Apple Inc. | Structured dictation using intelligent automated assistants |
US10152299B2 (en) | 2015-03-06 | 2018-12-11 | Apple Inc. | Reducing response latency of intelligent automated assistants |
US9911412B2 (en) | 2015-03-06 | 2018-03-06 | Nuance Communications, Inc. | Evidence-based natural language input recognition |
US10567477B2 (en) | 2015-03-08 | 2020-02-18 | Apple Inc. | Virtual assistant continuity |
US9721566B2 (en) | 2015-03-08 | 2017-08-01 | Apple Inc. | Competing devices responding to voice triggers |
US9886953B2 (en) | 2015-03-08 | 2018-02-06 | Apple Inc. | Virtual assistant activation |
US20160266871A1 (en) | 2015-03-11 | 2016-09-15 | Adapx, Inc. | Speech recognizer for multimodal systems and signing in/out with and /or for a digital pen |
US9805713B2 (en) | 2015-03-13 | 2017-10-31 | Google Inc. | Addressing missing features in models |
US9899019B2 (en) | 2015-03-18 | 2018-02-20 | Apple Inc. | Systems and methods for structured stem and suffix language models |
US20160286045A1 (en) | 2015-03-23 | 2016-09-29 | Vonage Network Llc | System and method for providing an informative message when rejecting an incoming call |
US10063510B2 (en) * | 2015-03-24 | 2018-08-28 | Facebook, Inc. | Techniques to share and remix media through a messaging system |
US9703394B2 (en) | 2015-03-24 | 2017-07-11 | Google Inc. | Unlearning techniques for adaptive language models in text entry |
US9672725B2 (en) | 2015-03-25 | 2017-06-06 | Microsoft Technology Licensing, Llc | Proximity-based reminders |
US20160284011A1 (en) | 2015-03-25 | 2016-09-29 | Facebook, Inc. | Techniques for social messaging authorization and customization |
US10261482B2 (en) | 2015-03-26 | 2019-04-16 | Ca, Inc. | Initiating actions on wearable devices |
TWI525532B (en) | 2015-03-30 | 2016-03-11 | Yu-Wei Chen | Set the name of the person to wake up the name for voice manipulation |
US9484021B1 (en) | 2015-03-30 | 2016-11-01 | Amazon Technologies, Inc. | Disambiguation in speech recognition |
US20170032783A1 (en) | 2015-04-01 | 2017-02-02 | Elwha Llc | Hierarchical Networked Command Recognition |
US10049099B2 (en) | 2015-04-10 | 2018-08-14 | Facebook, Inc. | Spell correction with hidden markov models on online social networks |
US9678664B2 (en) | 2015-04-10 | 2017-06-13 | Google Inc. | Neural network for keyboard input decoding |
US10095683B2 (en) | 2015-04-10 | 2018-10-09 | Facebook, Inc. | Contextual speller models on online social networks |
US10021209B2 (en) | 2015-04-10 | 2018-07-10 | Open Text Sa Ulc | Systems and methods for caching of managed content in a distributed environment using a multi-tiered architecture |
US9842105B2 (en) | 2015-04-16 | 2017-12-12 | Apple Inc. | Parsimonious continuous-space phrase representations for natural language processing |
KR102269035B1 (en) | 2015-04-21 | 2021-06-24 | 삼성전자주식회사 | Server and method for controlling a group action |
WO2016175354A1 (en) | 2015-04-29 | 2016-11-03 | 주식회사 아카인텔리전스 | Artificial intelligence conversation device and method |
GB2537903B (en) | 2015-04-30 | 2019-09-04 | Toshiba Res Europe Limited | Device and method for a spoken dialogue system |
US9953063B2 (en) | 2015-05-02 | 2018-04-24 | Lithium Technologies, Llc | System and method of providing a content discovery platform for optimizing social network engagements |
US20160328205A1 (en) | 2015-05-05 | 2016-11-10 | Motorola Mobility Llc | Method and Apparatus for Voice Operation of Mobile Applications Having Unnamed View Elements |
US9892363B2 (en) | 2015-05-07 | 2018-02-13 | Truemotion, Inc. | Methods and systems for sensor-based driving data collection |
US9953648B2 (en) | 2015-05-11 | 2018-04-24 | Samsung Electronics Co., Ltd. | Electronic device and method for controlling the same |
US9906482B2 (en) | 2015-05-13 | 2018-02-27 | The Travelers Indemnity Company | Predictive electronic message management systems and controllers |
US20160337299A1 (en) | 2015-05-13 | 2016-11-17 | Google Inc. | Prioritized notification display |
KR20160136013A (en) | 2015-05-19 | 2016-11-29 | 엘지전자 주식회사 | Mobile terminal and method for controlling the same |
US10861449B2 (en) | 2015-05-19 | 2020-12-08 | Sony Corporation | Information processing device and information processing method |
US10061848B2 (en) | 2015-05-22 | 2018-08-28 | Microsoft Technology Licensing, Llc | Ontology-crowd-relevance deep response generation |
US10097973B2 (en) | 2015-05-27 | 2018-10-09 | Apple Inc. | Systems and methods for proactively identifying and surfacing relevant content on a touch-sensitive device |
US10110430B2 (en) | 2015-05-27 | 2018-10-23 | Orion Labs | Intelligent agent features for wearable personal communication nodes |
US10200824B2 (en) | 2015-05-27 | 2019-02-05 | Apple Inc. | Systems and methods for proactively identifying and surfacing relevant content on a touch-sensitive device |
US10083688B2 (en) | 2015-05-27 | 2018-09-25 | Apple Inc. | Device voice control for selecting a displayed affordance |
US10127220B2 (en) | 2015-06-04 | 2018-11-13 | Apple Inc. | Language identification from short strings |
US10101822B2 (en) | 2015-06-05 | 2018-10-16 | Apple Inc. | Language input correction |
US9578173B2 (en) | 2015-06-05 | 2017-02-21 | Apple Inc. | Virtual assistant aided communication with 3rd party service in a communication session |
US10505884B2 (en) | 2015-06-05 | 2019-12-10 | Microsoft Technology Licensing, Llc | Entity classification and/or relationship identification |
US9865265B2 (en) | 2015-06-06 | 2018-01-09 | Apple Inc. | Multi-microphone speech recognition systems and related techniques |
US10255907B2 (en) | 2015-06-07 | 2019-04-09 | Apple Inc. | Automatic accent detection using acoustic models |
US20160357861A1 (en) | 2015-06-07 | 2016-12-08 | Apple Inc. | Natural language event detection |
US11025565B2 (en) | 2015-06-07 | 2021-06-01 | Apple Inc. | Personalized prediction of responses for instant messaging |
US10186254B2 (en) | 2015-06-07 | 2019-01-22 | Apple Inc. | Context-based endpoint detection |
US20160365101A1 (en) * | 2015-06-15 | 2016-12-15 | Motorola Mobility Llc | Enabling Event Driven Voice Interaction with a Device |
US20160371250A1 (en) | 2015-06-16 | 2016-12-22 | Microsoft Technology Licensing, Llc | Text suggestion using a predictive grammar model |
US20160372112A1 (en) | 2015-06-18 | 2016-12-22 | Amgine Technologies (Us), Inc. | Managing Interactions between Users and Applications |
US9767386B2 (en) | 2015-06-23 | 2017-09-19 | Adobe Systems Incorporated | Training a classifier algorithm used for automatically generating tags to be applied to images |
CN104951077A (en) | 2015-06-24 | 2015-09-30 | 百度在线网络技术(北京)有限公司 | Man-machine interaction method and device based on artificial intelligence and terminal equipment |
US10325590B2 (en) | 2015-06-26 | 2019-06-18 | Intel Corporation | Language model modification for local speech recognition systems using remote sources |
US20160379641A1 (en) | 2015-06-29 | 2016-12-29 | Microsoft Technology Licensing, Llc | Auto-Generation of Notes and Tasks From Passive Recording |
US20160378747A1 (en) | 2015-06-29 | 2016-12-29 | Apple Inc. | Virtual assistant for media playback |
US10019992B2 (en) | 2015-06-29 | 2018-07-10 | Disney Enterprises, Inc. | Speech-controlled actions based on keywords and context thereof |
US9536527B1 (en) | 2015-06-30 | 2017-01-03 | Amazon Technologies, Inc. | Reporting operational metrics in speech-based systems |
KR102371188B1 (en) | 2015-06-30 | 2022-03-04 | 삼성전자주식회사 | Apparatus and method for speech recognition, and electronic device |
US10073887B2 (en) | 2015-07-06 | 2018-09-11 | Conduent Business Services, Llc | System and method for performing k-nearest neighbor search based on minimax distance measure and efficient outlier detection |
US9998597B2 (en) | 2015-07-06 | 2018-06-12 | Nuance Communications, Inc. | Systems and methods for facilitating communication using an interactive communication system |
CN105100356B (en) | 2015-07-07 | 2018-04-06 | 上海斐讯数据通信技术有限公司 | The method and system that a kind of volume automatically adjusts |
JP2017019331A (en) | 2015-07-08 | 2017-01-26 | Ntn株式会社 | Motor driving device for vehicle |
US20170011303A1 (en) | 2015-07-09 | 2017-01-12 | Qualcomm Incorporated | Contact-Based Predictive Response |
US10249297B2 (en) | 2015-07-13 | 2019-04-02 | Microsoft Technology Licensing, Llc | Propagating conversational alternatives using delayed hypothesis binding |
US10426037B2 (en) | 2015-07-15 | 2019-09-24 | International Business Machines Corporation | Circuitized structure with 3-dimensional configuration |
US10311384B2 (en) | 2015-07-29 | 2019-06-04 | Microsoft Technology Licensing, Llc | Automatic creation and maintenance of a taskline |
US10255921B2 (en) | 2015-07-31 | 2019-04-09 | Google Llc | Managing dialog data providers |
US9691361B2 (en) | 2015-08-03 | 2017-06-27 | International Business Machines Corporation | Adjusting presentation of content on a display |
JP5906345B1 (en) | 2015-08-05 | 2016-04-20 | 株式会社Cygames | Program, electronic device, system and control method for predicting touch target based on operation history |
US10362978B2 (en) | 2015-08-28 | 2019-07-30 | Comcast Cable Communications, Llc | Computational model for mood |
US20170061423A1 (en) | 2015-09-01 | 2017-03-02 | Bank Of America Corporation | Use of wearable as an account control system |
US10747498B2 (en) | 2015-09-08 | 2020-08-18 | Apple Inc. | Zero latency digital assistant |
US10331312B2 (en) | 2015-09-08 | 2019-06-25 | Apple Inc. | Intelligent automated assistant in a media environment |
US10671428B2 (en) | 2015-09-08 | 2020-06-02 | Apple Inc. | Distributed personal assistant |
US10740384B2 (en) | 2015-09-08 | 2020-08-11 | Apple Inc. | Intelligent automated assistant for media search and playback |
US10026399B2 (en) | 2015-09-11 | 2018-07-17 | Amazon Technologies, Inc. | Arbitration between voice-enabled devices |
US9665567B2 (en) | 2015-09-21 | 2017-05-30 | International Business Machines Corporation | Suggesting emoji characters based on current contextual emotional state of user |
US9875081B2 (en) | 2015-09-21 | 2018-01-23 | Amazon Technologies, Inc. | Device selection for providing a response |
US9734142B2 (en) | 2015-09-22 | 2017-08-15 | Facebook, Inc. | Universal translation |
US20170085547A1 (en) | 2015-09-22 | 2017-03-23 | International Business Machines Corporation | Storing, indexing and recalling data based on brain activity |
US9990040B2 (en) | 2015-09-25 | 2018-06-05 | Immersion Corporation | Haptic CAPTCHA |
US11010550B2 (en) | 2015-09-29 | 2021-05-18 | Apple Inc. | Unified language modeling framework for word prediction, auto-completion and auto-correction |
US20170092278A1 (en) | 2015-09-30 | 2017-03-30 | Apple Inc. | Speaker recognition |
US11587559B2 (en) | 2015-09-30 | 2023-02-21 | Apple Inc. | Intelligent device identification |
US20170102837A1 (en) | 2015-10-07 | 2017-04-13 | Spotify Ab | Dynamic control of playlists using wearable devices |
US10083685B2 (en) | 2015-10-13 | 2018-09-25 | GM Global Technology Operations LLC | Dynamically adding or removing functionality to speech recognition systems |
US10891106B2 (en) | 2015-10-13 | 2021-01-12 | Google Llc | Automatic batch voice commands |
EP3369002A4 (en) | 2015-10-26 | 2019-06-12 | 24/7 Customer, Inc. | Method and apparatus for facilitating customer intent prediction |
US10146874B2 (en) | 2015-10-28 | 2018-12-04 | Fujitsu Limited | Refining topic representations |
US20170125016A1 (en) | 2015-11-02 | 2017-05-04 | Le Holdings (Beijing) Co., Ltd. | Method and electronic device for processing voice messages |
US9691378B1 (en) | 2015-11-05 | 2017-06-27 | Amazon Technologies, Inc. | Methods and devices for selectively ignoring captured audio data |
US10691473B2 (en) | 2015-11-06 | 2020-06-23 | Apple Inc. | Intelligent automated assistant in a messaging environment |
US10956666B2 (en) | 2015-11-09 | 2021-03-23 | Apple Inc. | Unconventional virtual assistant interactions |
US9804681B2 (en) | 2015-11-10 | 2017-10-31 | Motorola Mobility Llc | Method and system for audible delivery of notifications partially presented on an always-on display |
KR102432620B1 (en) | 2015-11-12 | 2022-08-16 | 삼성전자주식회사 | Electronic device and method for performing action according to proximity of external object |
US10255611B2 (en) | 2015-11-20 | 2019-04-09 | International Business Machines Corporation | Determining pricing using categorized costs with tree structures |
CN105897675A (en) | 2015-11-27 | 2016-08-24 | 乐视云计算有限公司 | Video service providing method, access authentication method, server and system |
KR102450853B1 (en) | 2015-11-30 | 2022-10-04 | 삼성전자주식회사 | Apparatus and method for speech recognition |
US10546015B2 (en) | 2015-12-01 | 2020-01-28 | Facebook, Inc. | Determining and utilizing contextual meaning of digital standardized image characters |
US10049668B2 (en) | 2015-12-02 | 2018-08-14 | Apple Inc. | Applying neural network language models to weighted finite state transducers for automatic speech recognition |
US10796693B2 (en) | 2015-12-09 | 2020-10-06 | Lenovo (Singapore) Pte. Ltd. | Modifying input based on determined characteristics |
US9990921B2 (en) | 2015-12-09 | 2018-06-05 | Lenovo (Singapore) Pte. Ltd. | User focus activated voice recognition |
US10685170B2 (en) | 2015-12-16 | 2020-06-16 | Microsoft Technology Licensing, Llc | Dynamic content layout generator |
US10223066B2 (en) | 2015-12-23 | 2019-03-05 | Apple Inc. | Proactive assistance based on dialog communication between devices |
AU2016383052A1 (en) | 2015-12-29 | 2018-06-28 | Mz Ip Holdings, Llc | Systems and methods for suggesting emoji |
US9716795B1 (en) | 2015-12-30 | 2017-07-25 | Qualcomm Incorporated | Diversion of a call to a wearable device |
US20170193083A1 (en) | 2016-01-06 | 2017-07-06 | International Business Machines Corporation | Identifying message content related to an event utilizing natural language processing and performing an action pertaining to the event |
US9792534B2 (en) | 2016-01-13 | 2017-10-17 | Adobe Systems Incorporated | Semantic natural language vector space |
US9747289B2 (en) | 2016-01-13 | 2017-08-29 | Disney Enterprises, Inc. | System and method for proximity-based personalized content recommendations |
CN105718448B (en) | 2016-01-13 | 2019-03-19 | 北京新美互通科技有限公司 | The method and apparatus that a kind of pair of input character carries out automatic translation |
US20170206899A1 (en) | 2016-01-20 | 2017-07-20 | Fitbit, Inc. | Better communication channel for requests and responses having an intelligent agent |
US9922647B2 (en) | 2016-01-29 | 2018-03-20 | International Business Machines Corporation | Approach to reducing the response time of a speech interface |
US10055489B2 (en) | 2016-02-08 | 2018-08-21 | Ebay Inc. | System and method for content-based media analysis |
US9858927B2 (en) | 2016-02-12 | 2018-01-02 | Amazon Technologies, Inc | Processing spoken commands to control distributed audio outputs |
US9965247B2 (en) | 2016-02-22 | 2018-05-08 | Sonos, Inc. | Voice controlled media playback system based on user profile |
US9820039B2 (en) | 2016-02-22 | 2017-11-14 | Sonos, Inc. | Default playback devices |
US9922648B2 (en) | 2016-03-01 | 2018-03-20 | Google Llc | Developer voice actions system |
US10404829B2 (en) | 2016-03-11 | 2019-09-03 | Wipro Limited | Method and system for achieving improved quality of service (QoS) for content delivery in a SDN controller based communication network |
US10446143B2 (en) | 2016-03-14 | 2019-10-15 | Apple Inc. | Identification of voice inputs providing credentials |
DK201670539A1 (en) | 2016-03-14 | 2017-10-02 | Apple Inc | Dictation that allows editing |
US10304444B2 (en) | 2016-03-23 | 2019-05-28 | Amazon Technologies, Inc. | Fine-grained natural language understanding |
US20170286397A1 (en) | 2016-03-30 | 2017-10-05 | International Business Machines Corporation | Predictive Embeddings |
US10979843B2 (en) | 2016-04-08 | 2021-04-13 | Qualcomm Incorporated | Spatialized audio output based on predicted position data |
US20170311005A1 (en) | 2016-04-26 | 2017-10-26 | Szu-Tung Lin | Method of wireless audio transmission and playback |
US10431205B2 (en) | 2016-04-27 | 2019-10-01 | Conduent Business Services, Llc | Dialog device with dialog support generated using a mixture of language models combined using a recurrent neural network |
US10235997B2 (en) | 2016-05-10 | 2019-03-19 | Google Llc | Voice-controlled closed caption display |
RU2632144C1 (en) | 2016-05-12 | 2017-10-02 | Общество С Ограниченной Ответственностью "Яндекс" | Computer method for creating content recommendation interface |
KR20170128820A (en) | 2016-05-16 | 2017-11-24 | 엘지전자 주식회사 | Mobile terminal and method for controlling the same |
US9934775B2 (en) | 2016-05-26 | 2018-04-03 | Apple Inc. | Unit-selection text-to-speech synthesis based on predicted concatenation parameters |
US9972304B2 (en) | 2016-06-03 | 2018-05-15 | Apple Inc. | Privacy preserving distributed evaluation framework for embedded personalized systems |
US10249300B2 (en) | 2016-06-06 | 2019-04-02 | Apple Inc. | Intelligent list reading |
US10049663B2 (en) | 2016-06-08 | 2018-08-14 | Apple, Inc. | Intelligent automated assistant for media exploration |
DK179309B1 (en) | 2016-06-09 | 2018-04-23 | Apple Inc | Intelligent automated assistant in a home environment |
US10586535B2 (en) | 2016-06-10 | 2020-03-10 | Apple Inc. | Intelligent digital assistant in a multi-tasking environment |
US10192552B2 (en) | 2016-06-10 | 2019-01-29 | Apple Inc. | Digital assistant providing whispered speech |
US10490187B2 (en) | 2016-06-10 | 2019-11-26 | Apple Inc. | Digital assistant providing automated status report |
US10067938B2 (en) | 2016-06-10 | 2018-09-04 | Apple Inc. | Multilingual word prediction |
US10127926B2 (en) | 2016-06-10 | 2018-11-13 | Google Llc | Securely executing voice actions with speaker identification and authentication input types |
US10509862B2 (en) | 2016-06-10 | 2019-12-17 | Apple Inc. | Dynamic phrase expansion of language input |
US10592601B2 (en) | 2016-06-10 | 2020-03-17 | Apple Inc. | Multilingual word prediction |
DK179343B1 (en) | 2016-06-11 | 2018-05-14 | Apple Inc | Intelligent task discovery |
DK201670540A1 (en) | 2016-06-11 | 2018-01-08 | Apple Inc | Application integration with a digital assistant |
DK179049B1 (en) | 2016-06-11 | 2017-09-18 | Apple Inc | Data driven natural language event detection and classification |
DK179415B1 (en) | 2016-06-11 | 2018-06-14 | Apple Inc | Intelligent device arbitration and control |
US11232136B2 (en) | 2016-06-27 | 2022-01-25 | Google Llc | Contextual voice search suggestions |
US9990176B1 (en) | 2016-06-28 | 2018-06-05 | Amazon Technologies, Inc. | Latency reduction for content playback |
US10200397B2 (en) | 2016-06-28 | 2019-02-05 | Microsoft Technology Licensing, Llc | Robust matching for identity screening |
US10491598B2 (en) | 2016-06-30 | 2019-11-26 | Amazon Technologies, Inc. | Multi-factor authentication to access services |
US10467114B2 (en) | 2016-07-14 | 2019-11-05 | International Business Machines Corporation | Hierarchical data processor tester |
US9825801B1 (en) | 2016-07-22 | 2017-11-21 | Spotify Ab | Systems and methods for using seektables to stream media items |
US9967382B2 (en) | 2016-08-19 | 2018-05-08 | Amazon Technologies, Inc. | Enabling voice control of telephone device |
US20180060312A1 (en) | 2016-08-23 | 2018-03-01 | Microsoft Technology Licensing, Llc | Providing ideogram translation |
US11200026B2 (en) | 2016-08-26 | 2021-12-14 | Bragi GmbH | Wireless earpiece with a passive virtual assistant |
US10313779B2 (en) | 2016-08-26 | 2019-06-04 | Bragi GmbH | Voice assistant system for wireless earpieces |
US10192551B2 (en) | 2016-08-30 | 2019-01-29 | Google Llc | Using textual input and user state information to generate reply content to present in response to the textual input |
CN107809372A (en) | 2016-09-08 | 2018-03-16 | 阿里巴巴集团控股有限公司 | The generation method of activity reminder message, movable based reminding method and device |
US10043516B2 (en) | 2016-09-23 | 2018-08-07 | Apple Inc. | Intelligent automated assistant |
KR20200035476A (en) | 2016-10-03 | 2020-04-03 | 구글 엘엘씨 | Processing voice commands based on device topology |
CN106484139B (en) | 2016-10-19 | 2019-01-29 | 北京新美互通科技有限公司 | Emoticon recommended method and device |
US10783883B2 (en) | 2016-11-03 | 2020-09-22 | Google Llc | Focus session at a voice interface device |
US10777201B2 (en) | 2016-11-04 | 2020-09-15 | Microsoft Technology Licensing, Llc | Voice enabled bot platform |
US10515632B2 (en) | 2016-11-15 | 2019-12-24 | At&T Intellectual Property I, L.P. | Asynchronous virtual assistant |
US10170110B2 (en) | 2016-11-17 | 2019-01-01 | Robert Bosch Gmbh | System and method for ranking of hybrid speech recognition results with neural networks |
US10332523B2 (en) | 2016-11-18 | 2019-06-25 | Google Llc | Virtual assistant identification of nearby computing devices |
KR20180060328A (en) | 2016-11-28 | 2018-06-07 | 삼성전자주식회사 | Electronic apparatus for processing multi-modal input, method for processing multi-modal input and sever for processing multi-modal input |
US9934785B1 (en) | 2016-11-30 | 2018-04-03 | Spotify Ab | Identification of taste attributes from an audio signal |
US10593346B2 (en) | 2016-12-22 | 2020-03-17 | Apple Inc. | Rank-reduced token representation for automatic speech recognition |
US10210864B2 (en) | 2016-12-29 | 2019-02-19 | T-Mobile Usa, Inc. | Voice command for communication between related devices |
US11204787B2 (en) | 2017-01-09 | 2021-12-21 | Apple Inc. | Application integration with a digital assistant |
US9747083B1 (en) | 2017-01-23 | 2017-08-29 | Essential Products, Inc. | Home device application programming interface |
US9980183B1 (en) | 2017-01-24 | 2018-05-22 | Essential Products, Inc. | Media and communications in a connected environment |
DE102017203570A1 (en) | 2017-03-06 | 2018-09-06 | Volkswagen Aktiengesellschaft | METHOD AND DEVICE FOR PRESENTING RECOMMENDED OPERATING OPERATIONS OF A PROPOSING SYSTEM AND INTERACTION WITH THE PROPOSING SYSTEM |
US10096319B1 (en) | 2017-03-13 | 2018-10-09 | Amazon Technologies, Inc. | Voice-based determination of physical and emotional characteristics of users |
US20180270343A1 (en) | 2017-03-20 | 2018-09-20 | Motorola Mobility Llc | Enabling event-driven voice trigger phrase on an electronic device |
US10547729B2 (en) | 2017-03-27 | 2020-01-28 | Samsung Electronics Co., Ltd. | Electronic device and method of executing function of electronic device |
US10282416B2 (en) | 2017-05-05 | 2019-05-07 | Apple Inc. | Unified framework for text conversion and prediction |
DK201770383A1 (en) | 2017-05-09 | 2018-12-14 | Apple Inc. | User interface for correcting recognition errors |
US10417266B2 (en) | 2017-05-09 | 2019-09-17 | Apple Inc. | Context-aware ranking of intelligent response suggestions |
DK201770439A1 (en) | 2017-05-11 | 2018-12-13 | Apple Inc. | Offline personal assistant |
US10726832B2 (en) | 2017-05-11 | 2020-07-28 | Apple Inc. | Maintaining privacy of personal information |
DK201770427A1 (en) | 2017-05-12 | 2018-12-20 | Apple Inc. | Low-latency intelligent automated assistant |
US20180330714A1 (en) | 2017-05-12 | 2018-11-15 | Apple Inc. | Machine learned systems |
US11301477B2 (en) | 2017-05-12 | 2022-04-12 | Apple Inc. | Feedback analysis of a digital assistant |
DK179496B1 (en) | 2017-05-12 | 2019-01-15 | Apple Inc. | USER-SPECIFIC Acoustic Models |
DK179745B1 (en) | 2017-05-12 | 2019-05-01 | Apple Inc. | SYNCHRONIZATION AND TASK DELEGATION OF A DIGITAL ASSISTANT |
DK201770411A1 (en) | 2017-05-15 | 2018-12-20 | Apple Inc. | Multi-modal interfaces |
DK201770432A1 (en) | 2017-05-15 | 2018-12-21 | Apple Inc. | Hierarchical belief states for digital assistants |
US10303715B2 (en) | 2017-05-16 | 2019-05-28 | Apple Inc. | Intelligent automated assistant for media exploration |
US11048995B2 (en) | 2017-05-16 | 2021-06-29 | Google Llc | Delayed responses by computational assistant |
US20180336892A1 (en) | 2017-05-16 | 2018-11-22 | Apple Inc. | Detecting a trigger of a digital assistant |
US10311144B2 (en) | 2017-05-16 | 2019-06-04 | Apple Inc. | Emoji word sense disambiguation |
DK179560B1 (en) | 2017-05-16 | 2019-02-18 | Apple Inc. | Far-field extension for digital assistant services |
US9967381B1 (en) | 2017-11-03 | 2018-05-08 | Republic Wireless, Inc. | Virtual telephony assistant |
CN107919123B (en) | 2017-12-07 | 2022-06-03 | 北京小米移动软件有限公司 | Multi-voice assistant control method, device and computer readable storage medium |
-
2015
- 2015-08-05 US US14/819,343 patent/US20160378747A1/en not_active Abandoned
-
2016
- 2016-03-31 EP EP16818374.7A patent/EP3289493A4/en not_active Withdrawn
- 2016-03-31 EP EP19180842.7A patent/EP3564831A1/en active Pending
- 2016-03-31 CN CN201680031457.6A patent/CN107615276B/en active Active
- 2016-03-31 WO PCT/US2016/025404 patent/WO2017003535A1/en active Application Filing
- 2016-03-31 CN CN202110585353.2A patent/CN113392239A/en active Pending
-
2019
- 2019-03-21 US US16/360,695 patent/US11010127B2/en active Active
-
2021
- 2021-04-09 US US17/226,988 patent/US20210224032A1/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8676904B2 (en) * | 2008-10-02 | 2014-03-18 | Apple Inc. | Electronic devices with voice command and contextual data processing capabilities |
US8739208B2 (en) * | 2009-02-12 | 2014-05-27 | Digimarc Corporation | Media processing methods and arrangements |
US20120192096A1 (en) * | 2011-01-25 | 2012-07-26 | Research In Motion Limited | Active command line driven user interface |
US20130332168A1 (en) * | 2012-06-08 | 2013-12-12 | Samsung Electronics Co., Ltd. | Voice activated search and control for applications |
US20130347029A1 (en) * | 2012-06-21 | 2013-12-26 | United Video Properties, Inc. | Systems and methods for navigating to content without an advertisement |
US20140040274A1 (en) * | 2012-07-31 | 2014-02-06 | Veveo, Inc. | Disambiguating user intent in conversational interaction system for large corpus information retrieval |
Cited By (268)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11671920B2 (en) | 2007-04-03 | 2023-06-06 | Apple Inc. | Method and system for operating a multifunction portable electronic device using voice-activation |
US11023513B2 (en) | 2007-12-20 | 2021-06-01 | Apple Inc. | Method and apparatus for searching using an active ontology |
US10381016B2 (en) | 2008-01-03 | 2019-08-13 | Apple Inc. | Methods and apparatus for altering audio output signals |
US9865248B2 (en) | 2008-04-05 | 2018-01-09 | Apple Inc. | Intelligent text-to-speech conversion |
US10108612B2 (en) | 2008-07-31 | 2018-10-23 | Apple Inc. | Mobile device having human language translation capability with positional feedback |
US11348582B2 (en) | 2008-10-02 | 2022-05-31 | Apple Inc. | Electronic devices with voice command and contextual data processing capabilities |
US10643611B2 (en) | 2008-10-02 | 2020-05-05 | Apple Inc. | Electronic devices with voice command and contextual data processing capabilities |
US11900936B2 (en) | 2008-10-02 | 2024-02-13 | Apple Inc. | Electronic devices with voice command and contextual data processing capabilities |
US10741185B2 (en) | 2010-01-18 | 2020-08-11 | Apple Inc. | Intelligent automated assistant |
US11423886B2 (en) | 2010-01-18 | 2022-08-23 | Apple Inc. | Task flow identification based on user intent |
US10692504B2 (en) | 2010-02-25 | 2020-06-23 | Apple Inc. | User profiling for voice input processing |
US10049675B2 (en) | 2010-02-25 | 2018-08-14 | Apple Inc. | User profiling for voice input processing |
US10417405B2 (en) | 2011-03-21 | 2019-09-17 | Apple Inc. | Device access using voice authentication |
US11120372B2 (en) | 2011-06-03 | 2021-09-14 | Apple Inc. | Performing actions associated with task items that represent tasks to perform |
US11350253B2 (en) | 2011-06-03 | 2022-05-31 | Apple Inc. | Active transport based notifications |
US11069336B2 (en) | 2012-03-02 | 2021-07-20 | Apple Inc. | Systems and methods for name pronunciation |
US11321116B2 (en) | 2012-05-15 | 2022-05-03 | Apple Inc. | Systems and methods for integrating third party services with a digital assistant |
US11269678B2 (en) | 2012-05-15 | 2022-03-08 | Apple Inc. | Systems and methods for integrating third party services with a digital assistant |
US10079014B2 (en) | 2012-06-08 | 2018-09-18 | Apple Inc. | Name recognition system |
US10978090B2 (en) | 2013-02-07 | 2021-04-13 | Apple Inc. | Voice trigger for a digital assistant |
US11862186B2 (en) | 2013-02-07 | 2024-01-02 | Apple Inc. | Voice trigger for a digital assistant |
US11636869B2 (en) | 2013-02-07 | 2023-04-25 | Apple Inc. | Voice trigger for a digital assistant |
US11557310B2 (en) | 2013-02-07 | 2023-01-17 | Apple Inc. | Voice trigger for a digital assistant |
US10714117B2 (en) | 2013-02-07 | 2020-07-14 | Apple Inc. | Voice trigger for a digital assistant |
US11388291B2 (en) | 2013-03-14 | 2022-07-12 | Apple Inc. | System and method for processing voicemail |
US11798547B2 (en) | 2013-03-15 | 2023-10-24 | Apple Inc. | Voice activated device for use with a voice-based digital assistant |
US9966060B2 (en) | 2013-06-07 | 2018-05-08 | Apple Inc. | System and method for user-specified pronunciation of words for speech synthesis and recognition |
US10657961B2 (en) | 2013-06-08 | 2020-05-19 | Apple Inc. | Interpreting and acting upon commands that involve sharing information with remote devices |
US11048473B2 (en) | 2013-06-09 | 2021-06-29 | Apple Inc. | Device, method, and graphical user interface for enabling conversation persistence across two or more instances of a digital assistant |
US10769385B2 (en) | 2013-06-09 | 2020-09-08 | Apple Inc. | System and method for inferring user intent from speech inputs |
US11727219B2 (en) | 2013-06-09 | 2023-08-15 | Apple Inc. | System and method for inferring user intent from speech inputs |
US11314370B2 (en) | 2013-12-06 | 2022-04-26 | Apple Inc. | Method for extracting salient dialog usage from live data |
US10108869B2 (en) * | 2014-05-23 | 2018-10-23 | Samsung Electronics Co., Ltd. | Method and device for reproducing content |
US20170249519A1 (en) * | 2014-05-23 | 2017-08-31 | Samsung Electronics Co., Ltd. | Method and device for reproducing content |
US10733466B2 (en) | 2014-05-23 | 2020-08-04 | Samsung Electronics Co., Ltd. | Method and device for reproducing content |
US11670289B2 (en) | 2014-05-30 | 2023-06-06 | Apple Inc. | Multi-command single utterance input method |
US10699717B2 (en) | 2014-05-30 | 2020-06-30 | Apple Inc. | Intelligent assistant for home automation |
US10714095B2 (en) | 2014-05-30 | 2020-07-14 | Apple Inc. | Intelligent assistant for home automation |
US10657966B2 (en) | 2014-05-30 | 2020-05-19 | Apple Inc. | Better resolution when referencing to concepts |
US10878809B2 (en) | 2014-05-30 | 2020-12-29 | Apple Inc. | Multi-command single utterance input method |
US11699448B2 (en) | 2014-05-30 | 2023-07-11 | Apple Inc. | Intelligent assistant for home automation |
US10417344B2 (en) | 2014-05-30 | 2019-09-17 | Apple Inc. | Exemplar-based natural language processing |
US10083690B2 (en) | 2014-05-30 | 2018-09-25 | Apple Inc. | Better resolution when referencing to concepts |
US11133008B2 (en) | 2014-05-30 | 2021-09-28 | Apple Inc. | Reducing the need for manual start/end-pointing and trigger phrases |
US11257504B2 (en) | 2014-05-30 | 2022-02-22 | Apple Inc. | Intelligent assistant for home automation |
US11810562B2 (en) | 2014-05-30 | 2023-11-07 | Apple Inc. | Reducing the need for manual start/end-pointing and trigger phrases |
US10497365B2 (en) | 2014-05-30 | 2019-12-03 | Apple Inc. | Multi-command single utterance input method |
US10904611B2 (en) | 2014-06-30 | 2021-01-26 | Apple Inc. | Intelligent automated assistant for TV user interactions |
US11516537B2 (en) | 2014-06-30 | 2022-11-29 | Apple Inc. | Intelligent automated assistant for TV user interactions |
US11838579B2 (en) | 2014-06-30 | 2023-12-05 | Apple Inc. | Intelligent automated assistant for TV user interactions |
US10431204B2 (en) | 2014-09-11 | 2019-10-01 | Apple Inc. | Method and apparatus for discovering trending terms in speech requests |
US10453443B2 (en) | 2014-09-30 | 2019-10-22 | Apple Inc. | Providing an indication of the suitability of speech recognition |
US10438595B2 (en) | 2014-09-30 | 2019-10-08 | Apple Inc. | Speaker identification and unsupervised speaker adaptation techniques |
US10390213B2 (en) | 2014-09-30 | 2019-08-20 | Apple Inc. | Social reminders |
US9986419B2 (en) | 2014-09-30 | 2018-05-29 | Apple Inc. | Social reminders |
US11231904B2 (en) | 2015-03-06 | 2022-01-25 | Apple Inc. | Reducing response latency of intelligent automated assistants |
US10930282B2 (en) | 2015-03-08 | 2021-02-23 | Apple Inc. | Competing devices responding to voice triggers |
US11087759B2 (en) | 2015-03-08 | 2021-08-10 | Apple Inc. | Virtual assistant activation |
US10529332B2 (en) | 2015-03-08 | 2020-01-07 | Apple Inc. | Virtual assistant activation |
US10311871B2 (en) | 2015-03-08 | 2019-06-04 | Apple Inc. | Competing devices responding to voice triggers |
US10567477B2 (en) | 2015-03-08 | 2020-02-18 | Apple Inc. | Virtual assistant continuity |
US11842734B2 (en) | 2015-03-08 | 2023-12-12 | Apple Inc. | Virtual assistant activation |
US11468282B2 (en) | 2015-05-15 | 2022-10-11 | Apple Inc. | Virtual assistant in a communication session |
US11127397B2 (en) | 2015-05-27 | 2021-09-21 | Apple Inc. | Device voice control |
US11070949B2 (en) | 2015-05-27 | 2021-07-20 | Apple Inc. | Systems and methods for proactively identifying and surfacing relevant content on an electronic device with a touch-sensitive display |
US10356243B2 (en) | 2015-06-05 | 2019-07-16 | Apple Inc. | Virtual assistant aided communication with 3rd party service in a communication session |
US10681212B2 (en) | 2015-06-05 | 2020-06-09 | Apple Inc. | Virtual assistant aided communication with 3rd party service in a communication session |
US11025565B2 (en) | 2015-06-07 | 2021-06-01 | Apple Inc. | Personalized prediction of responses for instant messaging |
US11010127B2 (en) | 2015-06-29 | 2021-05-18 | Apple Inc. | Virtual assistant for media playback |
US11003913B2 (en) * | 2015-09-07 | 2021-05-11 | Lg Electronics Inc. | Mobile terminal and method for operating the same |
US20190019035A1 (en) * | 2015-09-07 | 2019-01-17 | Lg Electronics Inc. | Mobile terminal and method for operating the same |
US11579699B1 (en) * | 2015-09-07 | 2023-02-14 | Oliver Markus Haynold | Hysteretic multilevel touch control |
US11126400B2 (en) | 2015-09-08 | 2021-09-21 | Apple Inc. | Zero latency digital assistant |
US11550542B2 (en) | 2015-09-08 | 2023-01-10 | Apple Inc. | Zero latency digital assistant |
US11500672B2 (en) | 2015-09-08 | 2022-11-15 | Apple Inc. | Distributed personal assistant |
US11853536B2 (en) | 2015-09-08 | 2023-12-26 | Apple Inc. | Intelligent automated assistant in a media environment |
US11809483B2 (en) | 2015-09-08 | 2023-11-07 | Apple Inc. | Intelligent automated assistant for media search and playback |
US20170083584A1 (en) * | 2015-09-23 | 2017-03-23 | Motorola Solutions, Inc. | Apparatus, system, and method for responding to a user-initiated query with a context-based response |
US11868354B2 (en) * | 2015-09-23 | 2024-01-09 | Motorola Solutions, Inc. | Apparatus, system, and method for responding to a user-initiated query with a context-based response |
US11809886B2 (en) | 2015-11-06 | 2023-11-07 | Apple Inc. | Intelligent automated assistant in a messaging environment |
US11526368B2 (en) | 2015-11-06 | 2022-12-13 | Apple Inc. | Intelligent automated assistant in a messaging environment |
US11886805B2 (en) | 2015-11-09 | 2024-01-30 | Apple Inc. | Unconventional virtual assistant interactions |
US10956666B2 (en) | 2015-11-09 | 2021-03-23 | Apple Inc. | Unconventional virtual assistant interactions |
US20180277133A1 (en) * | 2015-11-20 | 2018-09-27 | Synaptics Incorporated | Input/output mode control for audio processing |
US10354652B2 (en) | 2015-12-02 | 2019-07-16 | Apple Inc. | Applying neural network language models to weighted finite state transducers for automatic speech recognition |
US10942703B2 (en) | 2015-12-23 | 2021-03-09 | Apple Inc. | Proactive assistance based on dialog communication between devices |
US11853647B2 (en) | 2015-12-23 | 2023-12-26 | Apple Inc. | Proactive assistance based on dialog communication between devices |
US10492029B2 (en) * | 2016-01-21 | 2019-11-26 | Google Llc | Sharing navigation data among co-located computing devices |
US20180332432A1 (en) * | 2016-01-21 | 2018-11-15 | Google Llc | Sharing Navigation Data Among Co-Located Computing Devices |
US20190146994A1 (en) * | 2016-05-09 | 2019-05-16 | Audiocoup B.V. | System for determining user exposure to audio fragments |
US11227589B2 (en) | 2016-06-06 | 2022-01-18 | Apple Inc. | Intelligent list reading |
US11069347B2 (en) | 2016-06-08 | 2021-07-20 | Apple Inc. | Intelligent automated assistant for media exploration |
US10733993B2 (en) | 2016-06-10 | 2020-08-04 | Apple Inc. | Intelligent digital assistant in a multi-tasking environment |
US11657820B2 (en) | 2016-06-10 | 2023-05-23 | Apple Inc. | Intelligent digital assistant in a multi-tasking environment |
US11037565B2 (en) | 2016-06-10 | 2021-06-15 | Apple Inc. | Intelligent digital assistant in a multi-tasking environment |
US11809783B2 (en) | 2016-06-11 | 2023-11-07 | Apple Inc. | Intelligent device arbitration and control |
US10942702B2 (en) | 2016-06-11 | 2021-03-09 | Apple Inc. | Intelligent device arbitration and control |
US10580409B2 (en) | 2016-06-11 | 2020-03-03 | Apple Inc. | Application integration with a digital assistant |
US11749275B2 (en) | 2016-06-11 | 2023-09-05 | Apple Inc. | Application integration with a digital assistant |
US11152002B2 (en) | 2016-06-11 | 2021-10-19 | Apple Inc. | Application integration with a digital assistant |
US9990176B1 (en) * | 2016-06-28 | 2018-06-05 | Amazon Technologies, Inc. | Latency reduction for content playback |
US11237793B1 (en) * | 2016-06-28 | 2022-02-01 | Amazon Technologies, Inc. | Latency reduction for content playback |
US10474753B2 (en) | 2016-09-07 | 2019-11-12 | Apple Inc. | Language identification using recurrent neural networks |
US10553215B2 (en) | 2016-09-23 | 2020-02-04 | Apple Inc. | Intelligent automated assistant |
US10043516B2 (en) | 2016-09-23 | 2018-08-07 | Apple Inc. | Intelligent automated assistant |
US10891948B2 (en) | 2016-11-30 | 2021-01-12 | Spotify Ab | Identification of taste attributes from an audio signal |
US9934785B1 (en) * | 2016-11-30 | 2018-04-03 | Spotify Ab | Identification of taste attributes from an audio signal |
US11281993B2 (en) | 2016-12-05 | 2022-03-22 | Apple Inc. | Model and ensemble compression for metric learning |
US10593346B2 (en) | 2016-12-22 | 2020-03-17 | Apple Inc. | Rank-reduced token representation for automatic speech recognition |
US11656884B2 (en) | 2017-01-09 | 2023-05-23 | Apple Inc. | Application integration with a digital assistant |
US11204787B2 (en) | 2017-01-09 | 2021-12-21 | Apple Inc. | Application integration with a digital assistant |
US10073681B2 (en) | 2017-01-23 | 2018-09-11 | Essential Products, Inc. | Home device application programming interface |
US10297255B2 (en) | 2017-01-23 | 2019-05-21 | Bank Of America Corporation | Data processing system with machine learning engine to provide automated collaboration assistance functions |
US10365932B2 (en) | 2017-01-23 | 2019-07-30 | Essential Products, Inc. | Dynamic application customization for automated environments |
US10972297B2 (en) | 2017-01-23 | 2021-04-06 | Bank Of America Corporation | Data processing system with machine learning engine to provide automated collaboration assistance functions |
US9747083B1 (en) * | 2017-01-23 | 2017-08-29 | Essential Products, Inc. | Home device application programming interface |
US10031727B1 (en) * | 2017-01-23 | 2018-07-24 | Essential Products, Inc. | Home device application programming interface |
US10741181B2 (en) | 2017-05-09 | 2020-08-11 | Apple Inc. | User interface for correcting recognition errors |
US10332518B2 (en) | 2017-05-09 | 2019-06-25 | Apple Inc. | User interface for correcting recognition errors |
US10417266B2 (en) | 2017-05-09 | 2019-09-17 | Apple Inc. | Context-aware ranking of intelligent response suggestions |
US10847142B2 (en) | 2017-05-11 | 2020-11-24 | Apple Inc. | Maintaining privacy of personal information |
US11599331B2 (en) | 2017-05-11 | 2023-03-07 | Apple Inc. | Maintaining privacy of personal information |
US10726832B2 (en) | 2017-05-11 | 2020-07-28 | Apple Inc. | Maintaining privacy of personal information |
US10395654B2 (en) | 2017-05-11 | 2019-08-27 | Apple Inc. | Text normalization based on a data-driven learning network |
US10755703B2 (en) | 2017-05-11 | 2020-08-25 | Apple Inc. | Offline personal assistant |
US11467802B2 (en) | 2017-05-11 | 2022-10-11 | Apple Inc. | Maintaining privacy of personal information |
US10791176B2 (en) | 2017-05-12 | 2020-09-29 | Apple Inc. | Synchronization and task delegation of a digital assistant |
US11580990B2 (en) | 2017-05-12 | 2023-02-14 | Apple Inc. | User-specific acoustic models |
US10410637B2 (en) | 2017-05-12 | 2019-09-10 | Apple Inc. | User-specific acoustic models |
US11380310B2 (en) | 2017-05-12 | 2022-07-05 | Apple Inc. | Low-latency intelligent automated assistant |
US11301477B2 (en) | 2017-05-12 | 2022-04-12 | Apple Inc. | Feedback analysis of a digital assistant |
US11405466B2 (en) | 2017-05-12 | 2022-08-02 | Apple Inc. | Synchronization and task delegation of a digital assistant |
US11862151B2 (en) | 2017-05-12 | 2024-01-02 | Apple Inc. | Low-latency intelligent automated assistant |
US10789945B2 (en) | 2017-05-12 | 2020-09-29 | Apple Inc. | Low-latency intelligent automated assistant |
US11837237B2 (en) | 2017-05-12 | 2023-12-05 | Apple Inc. | User-specific acoustic models |
US11538469B2 (en) | 2017-05-12 | 2022-12-27 | Apple Inc. | Low-latency intelligent automated assistant |
US10810274B2 (en) | 2017-05-15 | 2020-10-20 | Apple Inc. | Optimizing dialogue policy decisions for digital assistants using implicit feedback |
US10482874B2 (en) | 2017-05-15 | 2019-11-19 | Apple Inc. | Hierarchical belief states for digital assistants |
US10909171B2 (en) | 2017-05-16 | 2021-02-02 | Apple Inc. | Intelligent automated assistant for media exploration |
US10748546B2 (en) | 2017-05-16 | 2020-08-18 | Apple Inc. | Digital assistant services based on device capabilities |
US11217255B2 (en) | 2017-05-16 | 2022-01-04 | Apple Inc. | Far-field extension for digital assistant services |
US10303715B2 (en) | 2017-05-16 | 2019-05-28 | Apple Inc. | Intelligent automated assistant for media exploration |
US11532306B2 (en) | 2017-05-16 | 2022-12-20 | Apple Inc. | Detecting a trigger of a digital assistant |
US10311144B2 (en) | 2017-05-16 | 2019-06-04 | Apple Inc. | Emoji word sense disambiguation |
US11675829B2 (en) * | 2017-05-16 | 2023-06-13 | Apple Inc. | Intelligent automated assistant for media exploration |
US10403278B2 (en) | 2017-05-16 | 2019-09-03 | Apple Inc. | Methods and systems for phonetic matching in digital assistant services |
WO2018212885A1 (en) * | 2017-05-16 | 2018-11-22 | Apple Inc. | Intelligent automated assistant for media exploration |
US20230259550A1 (en) * | 2017-05-16 | 2023-08-17 | Apple Inc. | Intelligent automated assistant for media exploration |
US20210165826A1 (en) * | 2017-05-16 | 2021-06-03 | Apple Inc. | Intelligent automated assistant for media exploration |
US10657328B2 (en) | 2017-06-02 | 2020-05-19 | Apple Inc. | Multi-task recurrent neural network architecture for efficient morphology handling in neural language modeling |
US10614122B2 (en) | 2017-06-09 | 2020-04-07 | Google Llc | Balance modifications of audio-based computer program output using a placeholder field based on content |
US10855627B2 (en) | 2017-06-09 | 2020-12-01 | Google Llc | Modification of audio-based computer program output |
US10600409B2 (en) | 2017-06-09 | 2020-03-24 | Google Llc | Balance modifications of audio-based computer program output including a chatbot selected based on semantic processing of audio |
US11582169B2 (en) * | 2017-06-09 | 2023-02-14 | Google Llc | Modification of audio-based computer program output |
US20210058347A1 (en) * | 2017-06-09 | 2021-02-25 | Google Llc | Modification of audio-based computer program output |
US10652170B2 (en) * | 2017-06-09 | 2020-05-12 | Google Llc | Modification of audio-based computer program output |
US10657173B2 (en) | 2017-06-09 | 2020-05-19 | Google Llc | Validate modification of audio-based computer program output |
US11017037B2 (en) | 2017-07-03 | 2021-05-25 | Google Llc | Obtaining responsive information from multiple corpora |
WO2019010138A1 (en) * | 2017-07-03 | 2019-01-10 | Google Llc | Obtaining responsive information from multiple corpora |
CN110770694A (en) * | 2017-07-03 | 2020-02-07 | 谷歌有限责任公司 | Obtaining response information from multiple corpora |
US10147426B1 (en) | 2017-08-01 | 2018-12-04 | Lenovo (Singapore) Pte. Ltd. | Method and device to select an audio output circuit based on priority attributes |
US11551691B1 (en) * | 2017-08-03 | 2023-01-10 | Wells Fargo Bank, N.A. | Adaptive conversation support bot |
US11854548B1 (en) | 2017-08-03 | 2023-12-26 | Wells Fargo Bank, N.A. | Adaptive conversation support bot |
US10803866B2 (en) | 2017-08-29 | 2020-10-13 | Baidu Online Network Technology (Beijing) Co., Ltd. | Interface intelligent interaction control method, apparatus and system, and storage medium |
CN107507615A (en) * | 2017-08-29 | 2017-12-22 | 百度在线网络技术(北京)有限公司 | Interface intelligent interaction control method, device, system and storage medium |
EP3451329A1 (en) * | 2017-08-29 | 2019-03-06 | Baidu Online Network Technology Beijing Co., Ltd. | Interface intelligent interaction control method, apparatus and system, and storage medium |
US10445429B2 (en) | 2017-09-21 | 2019-10-15 | Apple Inc. | Natural language understanding using vocabularies with compressed serialized tries |
US11526518B2 (en) | 2017-09-22 | 2022-12-13 | Amazon Technologies, Inc. | Data reporting system and method |
US20190095444A1 (en) * | 2017-09-22 | 2019-03-28 | Amazon Technologies, Inc. | Voice driven analytics |
US10755051B2 (en) | 2017-09-29 | 2020-08-25 | Apple Inc. | Rule-based natural language processing |
US10754615B2 (en) * | 2017-10-12 | 2020-08-25 | Hyundai Motor Company | Apparatus and method for processing user input for vehicle |
US20190114137A1 (en) * | 2017-10-12 | 2019-04-18 | Hyundai Motor Company | Apparatus and method for processing user input for vehicle |
US10636424B2 (en) | 2017-11-30 | 2020-04-28 | Apple Inc. | Multi-turn canned dialog |
US10685183B1 (en) * | 2018-01-04 | 2020-06-16 | Facebook, Inc. | Consumer insights analysis using word embeddings |
US10733982B2 (en) | 2018-01-08 | 2020-08-04 | Apple Inc. | Multi-directional dialog |
US10733375B2 (en) | 2018-01-31 | 2020-08-04 | Apple Inc. | Knowledge-based framework for improving natural language understanding |
US10789959B2 (en) | 2018-03-02 | 2020-09-29 | Apple Inc. | Training speaker recognition models for digital assistants |
US10909990B2 (en) | 2018-03-08 | 2021-02-02 | Frontive, Inc. | Methods and systems for speech signal processing |
US10460734B2 (en) * | 2018-03-08 | 2019-10-29 | Frontive, Inc. | Methods and systems for speech signal processing |
US11056119B2 (en) | 2018-03-08 | 2021-07-06 | Frontive, Inc. | Methods and systems for speech signal processing |
US10592604B2 (en) | 2018-03-12 | 2020-03-17 | Apple Inc. | Inverse text normalization for automatic speech recognition |
KR102635811B1 (en) * | 2018-03-19 | 2024-02-13 | 삼성전자 주식회사 | System and control method of system for processing sound data |
EP3543999A3 (en) * | 2018-03-19 | 2019-11-06 | Samsung Electronics Co., Ltd. | System for processing sound data and method of controlling system |
JP7317529B2 (en) | 2018-03-19 | 2023-07-31 | 三星電子株式会社 | SOUND DATA PROCESSING SYSTEM AND SYSTEM CONTROL METHOD |
KR20190109868A (en) * | 2018-03-19 | 2019-09-27 | 삼성전자주식회사 | System and control method of system for processing sound data |
CN110288987A (en) * | 2018-03-19 | 2019-09-27 | 三星电子株式会社 | Method for handling the system of voice data and controlling the system |
US11004451B2 (en) * | 2018-03-19 | 2021-05-11 | Samsung Electronics Co., Ltd | System for processing sound data and method of controlling system |
US10984799B2 (en) | 2018-03-23 | 2021-04-20 | Amazon Technologies, Inc. | Hybrid speech interface device |
US11437041B1 (en) | 2018-03-23 | 2022-09-06 | Amazon Technologies, Inc. | Speech interface device with caching component |
US10777203B1 (en) | 2018-03-23 | 2020-09-15 | Amazon Technologies, Inc. | Speech interface device with caching component |
US11887604B1 (en) | 2018-03-23 | 2024-01-30 | Amazon Technologies, Inc. | Speech interface device with caching component |
US11710482B2 (en) | 2018-03-26 | 2023-07-25 | Apple Inc. | Natural assistant interaction |
US10818288B2 (en) | 2018-03-26 | 2020-10-27 | Apple Inc. | Natural assistant interaction |
US10909331B2 (en) | 2018-03-30 | 2021-02-02 | Apple Inc. | Implicit identification of translation payload with neural machine translation |
US20210334306A1 (en) * | 2018-05-03 | 2021-10-28 | Google Llc | Coordination of overlapping processing of audio queries |
US10928918B2 (en) | 2018-05-07 | 2021-02-23 | Apple Inc. | Raise to speak |
US11487364B2 (en) | 2018-05-07 | 2022-11-01 | Apple Inc. | Raise to speak |
US11907436B2 (en) | 2018-05-07 | 2024-02-20 | Apple Inc. | Raise to speak |
US11169616B2 (en) | 2018-05-07 | 2021-11-09 | Apple Inc. | Raise to speak |
US11900923B2 (en) | 2018-05-07 | 2024-02-13 | Apple Inc. | Intelligent automated assistant for delivering content from user experiences |
US11854539B2 (en) | 2018-05-07 | 2023-12-26 | Apple Inc. | Intelligent automated assistant for delivering content from user experiences |
US11145294B2 (en) | 2018-05-07 | 2021-10-12 | Apple Inc. | Intelligent automated assistant for delivering content from user experiences |
US10984780B2 (en) | 2018-05-21 | 2021-04-20 | Apple Inc. | Global semantic word embeddings using bi-directional recurrent neural networks |
US11929088B2 (en) * | 2018-05-25 | 2024-03-12 | Synaptics Incorporated | Input/output mode control for audio processing |
US10984798B2 (en) | 2018-06-01 | 2021-04-20 | Apple Inc. | Voice interaction at a primary device to access call functionality of a companion device |
US10684703B2 (en) | 2018-06-01 | 2020-06-16 | Apple Inc. | Attention aware virtual assistant dismissal |
US11009970B2 (en) | 2018-06-01 | 2021-05-18 | Apple Inc. | Attention aware virtual assistant dismissal |
US10720160B2 (en) | 2018-06-01 | 2020-07-21 | Apple Inc. | Voice interaction at a primary device to access call functionality of a companion device |
US11431642B2 (en) | 2018-06-01 | 2022-08-30 | Apple Inc. | Variable latency device coordination |
US10403283B1 (en) | 2018-06-01 | 2019-09-03 | Apple Inc. | Voice interaction at a primary device to access call functionality of a companion device |
US11495218B2 (en) | 2018-06-01 | 2022-11-08 | Apple Inc. | Virtual assistant operation in multi-device environments |
US11360577B2 (en) | 2018-06-01 | 2022-06-14 | Apple Inc. | Attention aware virtual assistant dismissal |
US11386266B2 (en) | 2018-06-01 | 2022-07-12 | Apple Inc. | Text correction |
US10892996B2 (en) | 2018-06-01 | 2021-01-12 | Apple Inc. | Variable latency device coordination |
US11630525B2 (en) | 2018-06-01 | 2023-04-18 | Apple Inc. | Attention aware virtual assistant dismissal |
US10504518B1 (en) | 2018-06-03 | 2019-12-10 | Apple Inc. | Accelerated task performance |
US10944859B2 (en) | 2018-06-03 | 2021-03-09 | Apple Inc. | Accelerated task performance |
US10496705B1 (en) | 2018-06-03 | 2019-12-03 | Apple Inc. | Accelerated task performance |
CN112041787A (en) * | 2018-06-15 | 2020-12-04 | 三星电子株式会社 | Electronic device for outputting response to user input using application and method of operating the same |
US11010561B2 (en) | 2018-09-27 | 2021-05-18 | Apple Inc. | Sentiment prediction from textual data |
US11170166B2 (en) | 2018-09-28 | 2021-11-09 | Apple Inc. | Neural typographical error modeling via generative adversarial networks |
US11462215B2 (en) | 2018-09-28 | 2022-10-04 | Apple Inc. | Multi-modal inputs for voice commands |
US11893992B2 (en) | 2018-09-28 | 2024-02-06 | Apple Inc. | Multi-modal inputs for voice commands |
US10839159B2 (en) | 2018-09-28 | 2020-11-17 | Apple Inc. | Named entity normalization in a spoken dialog system |
US11475898B2 (en) | 2018-10-26 | 2022-10-18 | Apple Inc. | Low-latency multi-speaker speech recognition |
CN111225261A (en) * | 2018-11-27 | 2020-06-02 | Lg电子株式会社 | Multimedia device for processing voice command and control method thereof |
US10796695B2 (en) | 2018-11-27 | 2020-10-06 | Lg Electronics Inc. | Multimedia device for processing voice command |
EP3660841A1 (en) * | 2018-11-27 | 2020-06-03 | LG Electronics Inc. | Multimedia device for processing voice command |
US11638059B2 (en) | 2019-01-04 | 2023-04-25 | Apple Inc. | Content playback on multiple devices |
US11348573B2 (en) | 2019-03-18 | 2022-05-31 | Apple Inc. | Multimodality in digital assistant systems |
US11783815B2 (en) | 2019-03-18 | 2023-10-10 | Apple Inc. | Multimodality in digital assistant systems |
US11928604B2 (en) | 2019-04-09 | 2024-03-12 | Apple Inc. | Method and apparatus for building an intelligent automated assistant |
US11244267B2 (en) * | 2019-04-26 | 2022-02-08 | Dell Products L.P. | Digital fulfillment product onboarding system |
US11675491B2 (en) | 2019-05-06 | 2023-06-13 | Apple Inc. | User configurable task triggers |
US11217251B2 (en) | 2019-05-06 | 2022-01-04 | Apple Inc. | Spoken notifications |
US11475884B2 (en) | 2019-05-06 | 2022-10-18 | Apple Inc. | Reducing digital assistant latency when a language is incorrectly determined |
US11423908B2 (en) | 2019-05-06 | 2022-08-23 | Apple Inc. | Interpreting spoken requests |
US11705130B2 (en) | 2019-05-06 | 2023-07-18 | Apple Inc. | Spoken notifications |
US11307752B2 (en) | 2019-05-06 | 2022-04-19 | Apple Inc. | User configurable task triggers |
US11140099B2 (en) | 2019-05-21 | 2021-10-05 | Apple Inc. | Providing message response suggestions |
US11888791B2 (en) | 2019-05-21 | 2024-01-30 | Apple Inc. | Providing message response suggestions |
US11237797B2 (en) | 2019-05-31 | 2022-02-01 | Apple Inc. | User activity shortcut suggestions |
US11496600B2 (en) | 2019-05-31 | 2022-11-08 | Apple Inc. | Remote execution of machine-learned models |
US11360739B2 (en) | 2019-05-31 | 2022-06-14 | Apple Inc. | User activity shortcut suggestions |
US11289073B2 (en) | 2019-05-31 | 2022-03-29 | Apple Inc. | Device text to speech |
US11657813B2 (en) | 2019-05-31 | 2023-05-23 | Apple Inc. | Voice identification in digital assistant systems |
US11360641B2 (en) | 2019-06-01 | 2022-06-14 | Apple Inc. | Increasing the relevance of new available information |
US11790914B2 (en) | 2019-06-01 | 2023-10-17 | Apple Inc. | Methods and user interfaces for voice-based control of electronic devices |
US20210063190A1 (en) * | 2019-08-29 | 2021-03-04 | Subaru Corporation | Information processor, information processing method, audio output system, and computer-readable recording medium |
US11720614B2 (en) | 2019-09-06 | 2023-08-08 | Tata Consultancy Services Limited | Method and system for generating a response to an unstructured natural language (NL) query |
US11488406B2 (en) | 2019-09-25 | 2022-11-01 | Apple Inc. | Text detection using global geometry estimators |
US20210104220A1 (en) * | 2019-10-08 | 2021-04-08 | Sarah MENNICKEN | Voice assistant with contextually-adjusted audio output |
US11914848B2 (en) | 2020-05-11 | 2024-02-27 | Apple Inc. | Providing relevant data items based on context |
US11810578B2 (en) | 2020-05-11 | 2023-11-07 | Apple Inc. | Device arbitration for digital assistant-based intercom systems |
US11765209B2 (en) | 2020-05-11 | 2023-09-19 | Apple Inc. | Digital assistant hardware abstraction |
EP3910495A1 (en) * | 2020-05-12 | 2021-11-17 | Apple Inc. | Reducing description length based on confidence |
US11755276B2 (en) * | 2020-05-12 | 2023-09-12 | Apple Inc. | Reducing description length based on confidence |
US20210357172A1 (en) * | 2020-05-12 | 2021-11-18 | Apple Inc. | Reducing description length based on confidence |
WO2021231197A1 (en) * | 2020-05-12 | 2021-11-18 | Apple Inc. | Reducing description length based on confidence |
US11838734B2 (en) | 2020-07-20 | 2023-12-05 | Apple Inc. | Multi-device audio adjustment coordination |
US11750962B2 (en) | 2020-07-21 | 2023-09-05 | Apple Inc. | User identification using headphones |
US11696060B2 (en) | 2020-07-21 | 2023-07-04 | Apple Inc. | User identification using headphones |
US11501762B2 (en) * | 2020-07-29 | 2022-11-15 | Microsoft Technology Licensing, Llc | Compounding corrective actions and learning in mixed mode dictation |
US20220093101A1 (en) * | 2020-09-21 | 2022-03-24 | Amazon Technologies, Inc. | Dialog management for multiple users |
US11908468B2 (en) * | 2020-09-21 | 2024-02-20 | Amazon Technologies, Inc. | Dialog management for multiple users |
US20220137917A1 (en) * | 2020-10-30 | 2022-05-05 | Samsung Electronics Co., Ltd. | Method and system for assigning unique voice for electronic device |
US11924254B2 (en) | 2021-05-03 | 2024-03-05 | Apple Inc. | Digital assistant hardware abstraction |
US11515044B1 (en) * | 2021-12-31 | 2022-11-29 | Ix Innovation Llc | System for administering a qualitative assessment using an automated verbal interface |
Also Published As
Publication number | Publication date |
---|---|
US11010127B2 (en) | 2021-05-18 |
WO2017003535A1 (en) | 2017-01-05 |
EP3289493A4 (en) | 2019-01-09 |
US20210224032A1 (en) | 2021-07-22 |
CN113392239A (en) | 2021-09-14 |
EP3289493A1 (en) | 2018-03-07 |
US20190220246A1 (en) | 2019-07-18 |
CN107615276A (en) | 2018-01-19 |
EP3564831A1 (en) | 2019-11-06 |
CN107615276B (en) | 2021-05-28 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US11010127B2 (en) | Virtual assistant for media playback | |
US11675829B2 (en) | Intelligent automated assistant for media exploration | |
US11069347B2 (en) | Intelligent automated assistant for media exploration | |
US11755276B2 (en) | Reducing description length based on confidence | |
US11227589B2 (en) | Intelligent list reading | |
AU2017100581B4 (en) | Intelligent automated assistant for media exploration | |
US10249300B2 (en) | Intelligent list reading | |
US10152299B2 (en) | Reducing response latency of intelligent automated assistants | |
US10567477B2 (en) | Virtual assistant continuity | |
US20220374727A1 (en) | Intelligent device selection using historical interactions | |
EP3910495A1 (en) | Reducing description length based on confidence | |
US20230344537A1 (en) | Methods and systems for language processing with radio devices | |
US20230393872A1 (en) | Digital assistant integration with system interface | |
AU2018100133C4 (en) | Intelligent list reading | |
WO2021231197A1 (en) | Reducing description length based on confidence |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: APPLE INC., CALIFORNIA Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:ORR, RYAN M.;MANDEL, DANIEL J.;SINESIO, ANDREW J.;AND OTHERS;SIGNING DATES FROM 20150807 TO 20150811;REEL/FRAME:036342/0239 |
|
STCV | Information on status: appeal procedure |
Free format text: ON APPEAL -- AWAITING DECISION BY THE BOARD OF APPEALS |
|
STCV | Information on status: appeal procedure |
Free format text: APPEAL DISMISSED / WITHDRAWN |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: DOCKETED NEW CASE - READY FOR EXAMINATION |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: NON FINAL ACTION MAILED |
|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |