WO2022266209A2

WO2022266209A2 - Conversational and environmental transcriptions

Info

Publication number: WO2022266209A2
Application number: PCT/US2022/033607
Authority: WO
Inventors: Shiraz Akmal; Aaron Mackay BURNS; Brad Kenneth HERMAN
Original assignee: Apple Inc.
Priority date: 2021-06-16
Filing date: 2022-06-15
Publication date: 2022-12-22
Also published as: WO2022266209A3

Abstract

Systems and processes for transcriptions and transcription assistance are provided. For example, a textual representation of a conversation between a user and at least one conversation participant is obtained. Based on the textual representation, content associated with the conversation is identified, wherein the content includes at least one of a first input from the user and a second input from the at least one conversation participant. In response to a determination that the content is associated with predefined content, a portion of the textual representation is identified based on the content. Based on the identified portion, an output responsive to the at least one of the first input and the second input is provided.

Description

CONVERSATIONAL AND ENVIRONMENTAL TRANSCRIPTIONS

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Patent Application No. 63/211,219, filed June 16, 2021, titled “CONVERSATIONAL AND ENVIRONMENTAL TRANSCRIPTIONS,” the content of which is hereby incorporated by reference in its entirety for all purposes.

FIELD

[0002] The present disclosure relates generally to transcriptions and, more specifically, to the generation of and assistance with conversational and environmental transcriptions.

BACKGROUND

[0003] This disclosure describes techniques for generating transcriptions and providing proactive and reactive assistance with transcriptions. In general, transcriptions can be helpful to review and summarize information related to conversations or other interactions between parties. Given the increase of conversational communication between devices, and the technological advances of technology on such devices, conversational transcription can now be effectively utilized. In addition, various technologies may lend to effective translations with respect to an environment, such as an environment associated with extended reality or similar technologies.

[0004] However, conventional systems do not effectively provide proactive and reactive assistance based on these transcriptions, nor do such systems effectively generate transcriptions based on conversational context or environmental factors. For example, traditional systems do not offer users an efficient means by which to quickly review portions of a transcription based on specific parameters, such as conversational topics, environmental conditions, and the like. Such systems also do not offer user assistance based on a user’s attentive state, such as when the user becomes distracted from the conversation. Thus, an improved system for transcriptions and transcription assistance is desired. SUMMARY

[0005] Systems and processes for transcriptions and transcription assistance are provided. For example, a textual representation of a conversation between a user and at least one conversation participant is obtained. Based on the textual representation, content associated with the conversation is identified, wherein the content includes at least one of a first input from the user and a second input from the at least one conversation participant. In response to a determination that the content is associated with predefined content, a portion of the textual representation is identified based on the content. Based on the identified portion, an output responsive to the at least one of the first input and the second input is provided.

BRIEF DESCRIPTION OF THE DRAWINGS

[0006] FIG. 1 is a block diagram illustrating a system and environment for implementing a digital assistant, according to various examples.

[0007] FIG. 2A is a block diagram illustrating a portable multifunction device implementing the client-side portion of a digital assistant, according to various examples.

[0008] FIG. 2B is a block diagram illustrating exemplary components for event handling, according to various examples.

[0009] FIG. 3 illustrates a portable multifunction device implementing the client-side portion of a digital assistant, according to various examples.

[0010] FIG. 4 is a block diagram of an exemplary multifunction device with a display and a touch-sensitive surface, according to various examples.

[0011] FIG. 5 A illustrates an exemplary user interface for a menu of applications on a portable multifunction device, according to various examples.

[0012] 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.

[0013] FIG. 6A illustrates a personal electronic device, according to various examples.

[0014] FIG. 6B is a block diagram illustrating a personal electronic device, according to various examples. [0015] FIG. 7A is a block diagram illustrating a digital assistant system or a server portion thereof, according to various examples.

[0016] FIG. 7B illustrates the functions of the digital assistant shown in FIG. 7A, according to various examples.

[0017] FIG. 7C illustrates a portion of an ontology, according to various examples.

[0018] FIGS. 8A-8E illustrate a process for transcriptions and transcription assistance, according to various examples.

[0019] FIGS. 9A-9B illustrate a process for transcriptions and transcription assistance, according to various examples.

[0020] FIG. 10 illustrates a process for transcriptions and transcription assistance, according to various examples.

[0021] FIG. 11 illustrates a process for transcriptions and transcription assistance, according to various examples.

[0022] FIGS. 12A-12B illustrate a process for transcriptions and transcription assistance, according to various examples.

DETAILED DESCRIPTION

[0023] In the following description of examples, reference is made to the accompanying drawings in which are shown by way of illustration specific examples that can be practiced. It is to be understood that other examples can be used and structural changes can be made without departing from the scope of the various examples.

[0024] 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 input could be termed a second input, and, similarly, a second input could be termed a first input, without departing from the scope of the various described examples. The first input and the second input are both inputs and, in some cases, are separate and different inputs. [0025] The terminology used in the description of the various described examples herein is for the purpose of describing particular examples only and is not intended to be limiting.

As used in the description of the various described examples 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.

[0026] 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.

[0027] 1. System and Environment

[0028] FIG. 1 illustrates a block diagram of system 100 according to various examples.

In some examples, system 100 implements a digital assistant. The terms “digital assistant,” “virtual assistant,” “intelligent automated assistant,” or “automatic digital assistant” 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 performs 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.

[0029] Specifically, a digital assistant is 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 seeks either an informational answer or performance of a task by the digital assistant. A satisfactory response to the user request includes a provision of the requested informational answer, a performance of the requested task, or a combination of the two. For example, a user asks the digital assistant a question, such as “Where am I right now?” Based on the user’s current location, the digital assistant answers, “You are in Central Park near the west gate.” The user also requests 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 sometimes interacts 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 also provides responses in other visual or audio forms, e.g., as text, alerts, music, videos, animations, etc.

[0030] As shown in FIG. 1, in some examples, a digital assistant is implemented according to a client-server model. The digital assistant includes 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 communicates with DA server 106 through one or more networks 110. DA client 102 provides client-side functionalities such as user-facing input and output processing and communication with DA server 106. DA server 106 provides serverside functionalities for any number of DA clients 102 each residing on a respective user device 104.

[0031] In some examples, DA server 106 includes 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 facilitates the client-facing input and output processing for DA server 106. One or more processing modules 114 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. In some examples, DA server 106 communicates with external services 120 through network(s) 110 for task completion or information acquisition. I/O interface to external services 118 facilitates such communications. [0032] User device 104 can be any suitable electronic device. In some examples, user device 104 is 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 FIGS. 6A-6B). A portable multifunctional device is, for example, a mobile telephone that also contains other functions, such as PDA and/or music player functions. Specific examples of portable multifunction devices include the Apple Watch®, iPhone®, iPod Touch®, and iPad® devices from Apple Inc. of Cupertino, California. Other examples of portable multifunction devices include, without limitation, earphones/headphones, speakers, and laptop or tablet computers. Further, in some examples, user device 104 is a non-portable multifunctional device. In particular, user device 104 is a desktop computer, a game console, a speaker, a television, or a television set-top box. In some examples, user device 104 includes a touch-sensitive surface (e.g., touch screen displays and/or touchpads). Further, user device 104 optionally includes 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.

[0033] Examples of communication network(s) 110 include local area networks (LAN) and wide area networks (WAN), e.g., the Internet. Communication network(s) 110 is 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.

[0034] Server system 108 is implemented on one or more standalone data processing apparatus or a distributed network of computers. In some examples, server system 108 also employs 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.

[0035] In some examples, user device 104 communicates with DA server 106 via second user device 122. Second user device 122 is similar or identical to user device 104. For example, second user device 122 is similar to devices 200, 400, or 600 described below with reference to FIGS. 2A, 4, and 6A-6B. User device 104 is 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.

In some examples, second user device 122 is configured to act as a proxy between user device 104 and DA server 106. For example, DA client 102 of user device 104 is 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 processes the information and returns relevant data (e.g., data content responsive to the user request) to user device 104 via second user device 122

[0036] In some examples, user device 104 is 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 is 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, in some examples, includes any number and type of user devices configured in this proxy configuration to communicate with DA server system 106.

[0037] Although the digital assistant shown in FIG. 1 includes 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 are 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 is 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.

[0038] 2. Electronic Devices

[0039] 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 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. 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.

[0040] 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).

[0041] 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.

[0042] It should be appreciated that 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.

[0043] Memory 202 includes one or more computer-readable storage mediums. The computer-readable storage mediums are, for example, tangible and non-transitory. Memory 202 includes high-speed random access memory and also includes 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 controls access to memory 202 by other components of device 200.

[0044] In some examples, a non-transitory computer-readable storage medium of memory 202 is used to store instructions (e.g., for performing aspects of processes 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 of the processes described below) are stored on a non-transitory computer-readable storage medium (not shown) of the server system 108 or are divided between the non-transitory computer-readable storage medium of memory 202 and the non-transitory computer-readable storage medium of server system 108.

[0045] Peripherals interface 218 is 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. In some embodiments, peripherals interface 218, CPU 220, and memory controller 222 are implemented on a single chip, such as chip 204. In some other embodiments, they are implemented on separate chips. [0046] 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. The RF 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 802.11h, and/or IEEE 802.1 lac), 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.

[0047] 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 are retrieved from and/or transmitted to memory 202 and/or RF circuitry 208 by peripherals interface 218. In some embodiments, 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).

[0048] 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. In some alternate embodiments, input controlled 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 of speaker 211 and/or microphone 213. The one or more buttons optionally include a push button (e.g., 306, FIG. 3).

[0049] A quick press of the push button disengages 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 11/322,549, “Unlocking a Device by Performing Gestures on an Unlock Image,” filed December 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) turns power to device 200 on or off. The user is 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.

[0050] 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 includes graphics, text, icons, video, and any combination thereof (collectively termed “graphics”). In some embodiments, some or all of the visual output correspond to user- interface objects.

[0051] 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. In an exemplary embodiment, a point of contact between touch screen 212 and the user corresponds to a finger of the user.

[0052] Touch screen 212 uses 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 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. 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, California.

[0053] A touch-sensitive display in some embodiments of touch screen 212 is analogous to the multi-touch sensitive touchpads described in the following U.S. Patents: 6,323,846 (Westerman et al.), 6,570,557 (Westerman et al.), and/or 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 from device 200, whereas touch- sensitive touchpads do not provide visual output.

[0054] A touch-sensitive display in some embodiments of touch screen 212 is as described in the following applications: (1) U.S. Patent Application No. 11/381,313, “Multipoint Touch Surface Controller,” filed May 2, 2006; (2) U.S. Patent Application No. 10/840,862, “Multipoint Touchscreen,” filed May 6, 2004; (3) U.S. Patent Application No. 10/903,964, “Gestures For Touch Sensitive Input Devices,” filed July 30, 2004; (4) U.S. Patent Application No. 11/048,264, “Gestures For Touch Sensitive Input Devices,” filed January 31, 2005; (5) U.S. Patent Application No. 11/038,590, “Mode-Based Graphical User Interfaces For Touch Sensitive Input Devices,” filed January 18, 2005; (6) U S Patent Application No. 11/228,758, “Virtual Input Device Placement On A Touch Screen User Interface,” filed September 16, 2005; (7) U.S. Patent Application No. 11/228,700, “Operation Of A Computer With A Touch Screen Interface,” filed September 16, 2005; (8) U.S. Patent Application No. 11/228,737, “Activating Virtual Keys Of A Touch-Screen Virtual Keyboard,” filed September 16, 2005; and (9) U.S. Patent Application No. 11/367,749, “Multi-Functional Hand-Held Device,” filed March 3, 2006. All of these applications are incorporated by reference herein in their entirety.

[0055] Touch screen 212 has, for example, a video resolution in excess of 100 dpi. In some embodiments, the touch screen has a video resolution of approximately 160 dpi. The user makes contact with touch 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.

[0056] In some embodiments, in addition to the touch screen, device 200 includes 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 is a touch-sensitive surface that is separate from touch screen 212 or an extension of the touch-sensitive surface formed by the touch screen.

[0057] Device 200 also includes power system 262 for powering the various components. Power system 262 includes 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. [0058] Device 200 also includes 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 includes 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 captures still images or video. In some embodiments, 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 is 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 is obtained for video conferencing while the user views the other video conference participants on the touch screen display. In some embodiments, 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 is used along with the touch screen display for both video conferencing and still and/or video image acquisition.

[0059] 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 piezoresi stive 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 of device 200, opposite touch screen display 212, which is located on the front of device 200.

[0060] Device 200 also includes one or more proximity sensors 266. FIG. 2A shows proximity sensor 266 coupled to peripherals interface 218. Alternately, proximity sensor 266 is coupled to input controller 260 in I/O subsystem 206. Proximity sensor 266 is performed as described in U.S. Patent Application Nos. 11/241,839, “Proximity Detector In Handheld Device”; 11/240,788, “Proximity Detector In Handheld Device”; 11/620,702, “Using Ambient Light Sensor To Augment Proximity Sensor Output”; 11/586,862, “Automated Response To And Sensing Of User Activity In Portable Devices”; and 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 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).

[0061] 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. 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 of device 200, opposite touch screen display 212, which is located on the front of device 200.

[0062] Device 200 also includes one or more accelerometers 268. FIG. 2A shows accelerometer 268 coupled to peripherals interface 218. Alternately, accelerometer 268 is coupled to an input controller 260 in I/O subsystem 206. Accelerometer 268 performs, for example, 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) of device 200.

[0063] In some embodiments, 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. Further, memory 202 stores data and models, such as user data and models 231. Furthermore, in some embodiments, 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.

[0064] 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.

[0065] 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.) 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.

[0066] 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 fmger-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’Vmultiple finger contacts). In some embodiments, contact/motion module 230 and display controller 256 detect contact on a touchpad.

[0067] 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).

[0068] 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 fmger-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.

[0069] 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. 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.

[0070] 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 display controller 256.

[0071] 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.

[0072] Text input module 234, which is, in some examples, a component of graphics module 232, provides soft keyboards for entering text in various applications (e.g., contacts 237, email 240, IM 241, browser 247, and any other application that needs text input).

[0073] 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).

[0074] Digital assistant client module 229 includes various client-side digital assistant instructions to provide the client-side functionalities of the digital assistant. For example, digital assistant client module 229 is 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) 264, other input control devices 216, etc.) of portable multifunction device 200. Digital assistant client module 229 is also 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. For example, output is provided as voice, sound, alerts, text messages, menus, graphics, videos, animations, vibrations, and/or combinations of two or more of the above. During operation, digital assistant client module 229 communicates with DA server 106 using RF circuitry 208.

[0075] User data and models 231 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 include 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.

[0076] In some examples, digital assistant client module 229 utilizes 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. In some examples, digital assistant client module 229 provides the contextual information or a subset thereof with the user input to DA server 106 to help infer the user’s intent. In some examples, the digital assistant also uses the contextual information to determine how to prepare and deliver outputs to the user. Contextual information is referred to as context data.

[0077] In some examples, the contextual information that accompanies the user input includes 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 portable multifunction device 200 is provided to DA server 106 as contextual information associated with a user input. [0078] In some examples, the digital assistant client module 229 selectively provides information (e.g., user data 231) stored on the portable multifunction device 200 in response to requests from DA server 106. In some examples, digital assistant client module 229 also elicits 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 passes 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.

[0079] A more detailed description of a digital assistant is described below with reference to FIGS. 7A-C. It should be recognized that digital assistant client module 229 can include any number of the sub-modules of digital assistant module 726 described below.

[0080] Applications 236 include the following modules (or sets of instructions), or a subset or superset thereof:

[0081] Contacts module 237 (sometimes called an address book or contact list);

[0082] Telephone module 238;

[0083] Video conference module 239;

[0084] E-mail client module 240;

[0085] Instant messaging (IM) module 241;

[0086] Workout support module 242;

[0087] Camera module 243 for still and/or video images;

[0088] Image management module 244;

[0089] Video player module;

[0090] Music player module;

[0091] Browser module 247;

[0092] Calendar module 248; [0093] Widget modules 249, which includes, in some examples, 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;

[0094] Widget creator module 250 for making user-created widgets 249-6;

[0095] Search module 251 ;

[0096] Video and music player module 252, which merges video player module and music player module;

[0097] Notes module 253;

[0098] Map module 254; and/or

[0099] Online video module 255.

[0100] Examples of other applications 236 that are 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.

[0101] In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, contacts module 237 are 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.

[0102] 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, and text input module 234, telephone module 238 are 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. As noted above, the wireless communication uses any of a plurality of communications standards, protocols, and technologies.

[0103] 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, and telephone 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.

[0104] In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text 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 with image management module 244, 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.

[0105] In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, 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. In some embodiments, transmitted and/or received instant messages 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).

[0106] 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.

[0107] In conjunction with touch screen 212, display controller 256, optical sensor(s)

264, optical sensor controller 258, contact/motion module 230, graphics module 232, and image management module 244, 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.

[0108] In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, and camera 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.

[0109] In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text 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.

[0110] 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, and browser 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.

[0111] In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, and browser module 247, widget modules 249 are mini-applications that can 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).

[0112] In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, and browser module 247, the widget creator module 250 are used by a user to create widgets (e.g., turning a user- specified portion of a web page into a widget).

[0113] In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, 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.

[0114] In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, audio circuitry 210, speaker 211, RF circuitry 208, and browser module 247, 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). In some embodiments, device 200 optionally includes the functionality of an MP3 player, such as an iPod (trademark of Apple Inc.).

[0115] In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, notes module 253 includes executable instructions to create and manage notes, to-do lists, and the like in accordance with user instructions.

[0116] 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, and browser module 247, map module 254 are 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. [0117] 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, and browser 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 than e-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 June 20, 2007, and U.S. Patent Application No. 11/968,067, “Portable Multifunction Device, Method, and Graphical User Interface for Playing Online Videos,” filed December 31, 2007, the contents of which are hereby incorporated by reference in their entirety.

[0118] 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 can be combined or otherwise rearranged in various embodiments. For example, video player module can 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 stores a subset of the modules and data structures identified above. Furthermore, memory 202 stores additional modules and data structures not described above.

[0119] 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 of device 200, the number of physical input control devices (such as push buttons, dials, and the like) on device 200 is reduced.

[0120] 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 on device 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.

[0121] 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).

[0122] 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. In some embodiments, 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. In some embodiments, 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.

[0123] 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.

[0124] 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. [0125] 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).

[0126] In some embodiments, event sorter 270 also includes a hit view determination module 272 and/or an active event recognizer determination module 273.

[0127] 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.

[0128] 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 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 is called the hit view, and the set of events that are recognized as proper inputs is determined based, at least in part, on the hit view of the initial touch that begins a touch-based gesture.

[0129] 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, 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). Once the hit view is identified by the hit view 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.

[0130] 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.

[0131] 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.

[0132] In some embodiments, operating system 226 includes event sorter 270. Alternatively, application 236-1 includes event sorter 270. In yet other embodiments, event sorter 270 is a stand-alone module, or a part of another module stored in memory 202, such as contact/motion module 230.

[0133] 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. Each application view 291 of the application 236-1 includes one or more event recognizers 280. Typically, a respective application view 291 includes a plurality of event recognizers 280. In other embodiments, 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. In some embodiments, 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 utilizes or calls data updater 276, object updater 277, or GUI updater 278 to update the application internal state 292. Alternatively, one or more of the application views 291 include one or more respective event handlers 290. Also, in some embodiments, one or more of data updater 276, object updater 277, and GUI updater 278 are included in a respective application view 291.

[0134] 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. In some embodiments, event recognizer 280 also includes at least a subset of: metadata 283, and event delivery instructions 288 (which include sub-event delivery instructions)

[0135] 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. 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 also includes 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.

[0136] 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 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. 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 associated event handlers 290.

[0137] 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 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

[0138] 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.

[0139] When 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.

[0140] In some embodiments, 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. In some embodiments, metadata 283 includes configurable properties, flags, and/or lists that indicate how event recognizers 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.

[0141] In some embodiments, 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. In some embodiments, 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. In some embodiments, 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. [0142] 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

[0143] 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 in contacts module 237, or stores a video file used in video player module. In some embodiments, object updater 277 creates and updates objects used in application 236-1. For example, object updater 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 to graphics module 232 for display on a touch- sensitive display.

[0144] In some embodiments, event handler(s) 290 includes or has access to data updater 276, object updater 277, and GUI updater 278. In some embodiments, 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.

[0145] 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.

[0146] 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. 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 with device 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.

[0147] Device 200 also includes one or more physical buttons, such as “home” or menu button 304. As described previously, menu button 304 is used to navigate to any application 236 in a set of applications that is executed on device 200. Alternatively, in some embodiments, the menu button is implemented as a soft key in a GUI displayed on touch screen 212.

[0148] In one embodiment, 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. In an alternative embodiment, 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.

[0149] 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 or other communications interfaces 460, memory 470, and one or more 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 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).

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. For example, 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.

[0150] Each of the above-identified elements in FIG. 4 is, in some examples, 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 are combined or otherwise rearranged in various embodiments. In some embodiments, memory 470 stores a subset of the modules and data structures identified above. Furthermore, memory 470 stores additional modules and data structures not described above. [0151] Attention is now directed towards embodiments of user interfaces that can be implemented on, for example, portable multifunction device 200.

[0152] 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 are implemented on device 400. In some embodiments, user interface 500 includes the following elements, or a subset or superset thereof:

[0153] Signal strength indicator(s) 502 for wireless communication(s), such as cellular and Wi-Fi signals;

[0154] Time 504;

[0155] Bluetooth indicator 505;

[0156] Battery status indicator 506;

[0157] Tray 508 with icons for frequently used applications, such as:

[0158] Icon 516 for telephone module 238, labeled “Phone,” which optionally includes an indicator 514 of the number of missed calls or voicemail messages;

[0159] Icon 518 for e-mail client module 240, labeled “Mail,” which optionally includes an indicator 510 of the number of unread e-mails;

[0160] Icon 520 for browser module 247, labeled “Browser;” and

[0161] Icon 522 for video and music player module 252, also referred to as iPod

(trademark of Apple Inc.) module 252, labeled “iPod;” and

[0162] Icons for other applications, such as:

[0163] Icon 524 for IM module 241, labeled “Messages;”

[0164] Icon 526 for calendar module 248, labeled “Calendar;”

[0165] Icon 528 for image management module 244, labeled “Photos;”

[0166] Icon 530 for camera module 243, labeled “Camera;” [0167] Icon 532 for online video module 255, labeled “Online Video;”

[0168] Icon 534 for stocks widget 249-2, labeled “Stocks;”

[0169] Icon 536 for map module 254, labeled “Maps;”

[0170] Icon 538 for weather widget 249-1, labeled “Weather;”

[0171] Icon 540 for alarm clock widget 249-4, labeled “Clock;”

[0172] Icon 542 for workout support module 242, labeled “Workout Support;”

[0173] Icon 544 for notes module 253, labeled “Notes;” and

[0174] Icon 546 for a settings application or module, labeled “Settings,” which provides access to settings for device 200 and its various applications 236.

[0175] It should be noted that the icon labels illustrated in FIG. 5A are merely exemplary. For example, icon 522 for video and music player module 252 is optionally 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.

[0176] 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 459) for detecting intensity of contacts on touch-sensitive surface 551 and/or one or more tactile output generators 457 for generating tactile outputs for a user of device 400.

[0177] 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 in FIG. 5B) 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). In accordance with these embodiments, the device detects contacts (e.g., 560 and 562 in FIG. 5B) with the touch- sensitive surface 551 at locations that correspond to respective locations on the display (e.g., in FIG. 5B, 560 corresponds to 568 and 562 corresponds to 570). In this way, user inputs (e.g., contacts 560 and 562, and movements thereof) detected by the device on the touch- sensitive surface (e.g., 551 in FIG. 5B) are used by the device to manipulate the user interface on the display (e.g., 550 in FIG. 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.

[0178] 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.

[0179] FIG. 6A illustrates exemplary personal electronic device 600. Device 600 includes body 602. In some embodiments, device 600 includes some or all of the features described with respect to devices 200 and 400 (e.g., FIGS. 2A-4). In some embodiments, device 600 has touch-sensitive display screen 604, hereafter touch screen 604. Alternatively, or in addition to touch screen 604, device 600 has a display and a touch-sensitive surface. As with devices 200 and 400, in some embodiments, touch screen 604 (or the touch-sensitive surface) has 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) provide output data that represents the intensity of touches. The user interface of device 600 responds to touches based on their intensity, meaning that touches of different intensities can invoke different user interface operations on device 600.

[0180] Techniques for detecting and processing touch intensity are 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 November 11, 2013, each of which is hereby incorporated by reference in their entirety.

[0181] In some embodiments, device 600 has one or more input mechanisms 606 and 608. Input mechanisms 606 and 608, if included, are physical. Examples of physical input mechanisms include push buttons and rotatable mechanisms. In some embodiments, 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 permit device 600 to be worn by a user.

[0182] FIG. 6B depicts exemplary personal electronic device 600. In some embodiments, device 600 includes some or all of the components described with respect to FIGS. 2A, 2B, and 4. Device 600 has bus 612 that operatively couples EO section 614 with one or more computer processors 616 and memory 618. I/O section 614 is connected to display 604, which can have touch-sensitive component 622 and, optionally, touch-intensity sensitive component 624. In addition, I/O section 614 is 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 includes input mechanisms 606 and/or 608. Input mechanism 606 is a rotatable input device or a depressible and rotatable input device, for example. Input mechanism 608 is a button, in some examples.

[0183] Input mechanism 608 is a microphone, in some examples. Personal electronic device 600 includes, for example, 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 are operatively connected to EO section 614.

[0184] Memory 618 of personal electronic device 600 is a non-transitory computer- readable storage medium, for storing computer-executable instructions, which, when executed by one or more computer processors 616, for example, cause the computer processors to perform the techniques and processes described below. The computer- executable instructions, for example, are also 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. 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.

[0185] As used here, the term “affordance” refers to a user-interactive graphical user interface object that is, for example, displayed on the display screen of devices 200, 400, and/or 600 (FIGS. 2A, 4, and 6A-6B). For example, an image (e.g., icon), a button, and text (e.g., hyperlink) each constitutes an affordance.

[0186] 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 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. In some implementations that include a touch screen display (e.g., touch-sensitive display system 212 in FIG. 2A or touch screen 212 in FIG. 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).

[0187] 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 includes 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.

[0188] In some embodiments, a portion of a gesture is identified for purposes of determining a characteristic intensity. For example, a touch-sensitive surface receives 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 is 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 is 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.

[0189] The intensity of a contact on the touch-sensitive surface is 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.

[0190] 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.

[0191] 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).

[0192] 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).

[0193] 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.

[0194] 3. Digital Assistant System

[0195] FIG. 7A illustrates a block diagram of digital assistant system 700 in accordance with various examples. In some examples, digital assistant system 700 is implemented on a standalone computer system. In some examples, digital assistant system 700 is distributed across multiple computers. In some examples, some of the modules and functions of the digital assistant are 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. In some examples, digital assistant system 700 is an implementation of server system 108 (and/or DA server 106) shown in FIG. 1. It should be noted that 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, can combine two or more components, or can have a different configuration or arrangement of the components. The various components shown in FIG. 7A are 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.

[0196] Digital assistant system 700 includes 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.

[0197] In some examples, memory 702 includes 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).

[0198] In some examples, I/O interface 706 couples 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, receives 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 includes 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. In some examples, digital assistant system 700 represents 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).

[0199] In some examples, the network communications interface 708 includes wired communication port(s) 712 and/or wireless transmission and reception circuitry 714. The wired communication port(s) receives and send communication signals via one or more wired interfaces, e.g., Ethernet, Universal Serial Bus (USB), FIREWIRE, etc. The wireless circuitry 714 receives and sends RF signals and/or optical signals from/to communications networks and other communications devices. The wireless communications 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 enables 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.

[0200] In some examples, memory 702, or the computer-readable storage media of memory 702, stores 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. In particular, memory 702, or the computer-readable storage media of memory 702, stores instructions for performing the processes described below. One or more processors 704 execute these programs, modules, and instructions, and reads/writes from/to the data structures.

[0201] Operating system 718 (e g., Darwin, RTXC, LINUX, UNIX, iOS, OS X, 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 communications between various hardware, firmware, and software components.

[0202] Communications module 720 facilitates communications between digital assistant system 700 with other devices over network communications interface 708. For example, communications module 720 communicates with RF circuitry 208 of electronic devices such as devices 200, 400, and 600 shown in FIGS. 2A, 4, 6A-6B, respectively. Communications module 720 also includes various components for handling data received by wireless circuitry 714 and/or wired communications port 712.

[0203] User interface module 722 receives commands and/or inputs from a user via EO 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 also prepares and delivers 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.). [0204] Applications 724 include programs and/or modules that are configured to be executed by one or more processors 704. For example, if the digital assistant system is implemented on a standalone user device, applications 724 include user applications, such as games, a calendar application, a navigation application, or an email application. If digital assistant system 700 is implemented on a server, applications 724 include resource management applications, diagnostic applications, or scheduling applications, for example.

[0205] Memory 702 also stores digital assistant module 726 (or the server portion of a digital assistant). In some examples, digital assistant module 726 includes 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 processing module 740. Each of these modules has 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 758.

[0206] 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.

[0207] In some examples, as shown in FIG. 7B, I/O processing module 728 interacts 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 optionally obtains 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 includes 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 also sends 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 includes speech input, I/O processing module 728 forwards the speech input to STT processing module 730 (or speech recognizer) for speech-to-text conversions.

[0208] STT processing module 730 includes one or more ASR systems 758. The one or more ASR systems 758 can process the speech input that is received through I/O processing module 728 to produce a recognition result. Each ASR system 758 includes a front-end speech pre-processor. The front-end speech pre-processor extracts representative features from the speech input. For example, the front-end speech pre-processor performs 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 758 includes one or more speech recognition models (e.g., acoustic models and/or language models) and implements one or more speech recognition engines. Examples of speech recognition models include Hidden Markov Models, Gaussian-Mixture Models, Deep Neural Network Models, n-gram language models, and other statistical models. Examples of speech recognition engines 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 are 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 is 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. Once 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 is passed to natural language processing module 732 for intent deduction. In some examples, STT processing module 730 produces multiple candidate text representations of the speech input. Each candidate text representation is a sequence of words or tokens corresponding to the speech input. In some examples, each candidate text representation is associated with a speech recognition confidence score. Based on the speech recognition confidence scores, STT processing module 730 ranks the candidate text representations and provides the n-best (e.g., n highest ranked) candidate text representation(s) to natural language processing module 732 for intent deduction, where n is a predetermined integer greater than zero. For example, in one example, only the highest ranked (n=l) candidate text representation is passed to natural language processing module 732 for intent deduction. In another example, the five highest ranked (n=5) candidate text representations are passed to natural language processing module 732 for intent deduction.

[0209] More details on the speech-to-text processing are described in U.S. Utility Application Serial No. 13/236,942 for “Consolidating Speech Recognition Results,” filed on September 20, 2011, the entire disclosure of which is incorporated herein by reference.

[0210] In some examples, STT processing module 730 includes and/or accesses a vocabulary of recognizable words via phonetic alphabet conversion module 731. Each vocabulary word is associated with one or more candidate pronunciations of the word represented in a speech recognition phonetic alphabet. In particular, the vocabulary of recognizable words includes a word that is associated with a plurality of candidate pronunciations. For example, the vocabulary includes the word “tomato” that is associated with the candidate pronunciations of /to'meirou/ and /to'matou/. Further, vocabulary words are associated with custom candidate pronunciations that are based on previous speech inputs from the user. Such custom candidate pronunciations are stored in STT processing module 730 and are associated with a particular user via the user’s profile on the device. In some examples, the candidate pronunciations for words are determined based on the spelling of the word and one or more linguistic and/or phonetic rules. In some examples, the candidate pronunciations are manually generated, e.g., based on known canonical pronunciations.

[0211] In some examples, the candidate pronunciations are ranked based on the commonness of the candidate pronunciation. For example, the candidate pronunciation /to'meirou/ is ranked higher than /to'matou/, 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 are ranked based on whether the candidate pronunciation is a custom candidate pronunciation associated with the user. For example, custom candidate pronunciations are 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 are associated with one or more speech characteristics, such as geographic origin, nationality, or ethnicity. For example, the candidate pronunciation /to'meifou/ is associated with the United States, whereas the candidate pronunciation /to'matou/ is associated with Great Britain. Further, the rank of the candidate pronunciation is 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 /to'meirou/ (associated with the United States) is ranked higher than the candidate pronunciation /to'matou/ (associated with Great Britain). In some examples, one of the ranked candidate pronunciations is selected as a predicted pronunciation (e.g., the most likely pronunciation).

[0212] When a speech input is received, STT processing module 730 is 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 first identifies the sequence of phonemes /to'meirou/ 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.”

[0213] In some examples, STT processing module 730 uses approximate matching techniques to determine words in an utterance. Thus, for example, the STT processing module 730 determines that the sequence of phonemes /to'meirou/ corresponds to the word “tomato,” even if that particular sequence of phonemes is not one of the candidate sequence of phonemes for that word.

[0214] Natural language processing module 732 (“natural language processor”) of the digital assistant takes the n-best candidate text representation(s) (“word sequence(s)” or “token sequence(s)”) generated by STT processing module 730, and attempts to associate each of the candidate text representations with one or more “actionable intents” recognized by the digital assistant. An “actionable intent” (or “user intent”) represents 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 is 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 is 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, however, also dependents on the assistant’s ability to infer the correct “actionable intent(s)” from the user request expressed in natural language. [0215] In some examples, in addition to the sequence of words or tokens obtained from STT processing module 730, natural language processing module 732 also receives contextual information associated with the user request, e ., from I/O processing module 728. The natural language processing module 732 optionally uses the contextual information to clarify, supplement, and/or further define the information contained in the candidate text representations received from STT processing module 730. The contextual information includes, 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 is, in some examples, dynamic, and changes with time, location, content of the dialogue, and other factors.

[0216] In some examples, the natural language processing is based on, e.g., ontology 760. Ontology 760 is 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” represents a task that the digital assistant is capable of performing, i.e., it is “actionable” or can be acted on. A “property” represents 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 defines how a parameter represented by the property node pertains to the task represented by the actionable intent node.

[0217] In some examples, ontology 760 is made up of actionable intent nodes and property nodes. Within ontology 760, each actionable intent node is linked to one or more property nodes either directly or through one or more intermediate property nodes. Similarly, each property node is linked to one or more actionable intent nodes either directly or through one or more intermediate property nodes. For example, as shown in FIG. 7C, ontology 760 includes a “restaurant reservation” node (i.e., an actionable intent node). Property nodes “restaurant,” “date/time” (for the reservation), and “party size” are each directly linked to the actionable intent node (i.e., the “restaurant reservation” node).

[0218] In addition, property nodes “cuisine,” “price range,” “phone number,” and “location” are sub-nodes of the property node “restaurant,” and are each 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 also includes a “set reminder” node (i.e., another actionable intent node). Property nodes “date/time” (for setting the reminder) and “subject” (for the reminder) are each linked to the “set reminder” node. Since the property “date/time” is relevant to both the task of making a restaurant reservation and the task of setting a reminder, the property node “date/time” is linked to both the “restaurant reservation” node and the “set reminder” node in ontology 760.

[0219] An actionable intent node, along with its linked property nodes, is described as a “domain.” In the present discussion, each domain is 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 in FIG. 7C includes 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 includes the actionable intent node “set reminder,” and property nodes “subject” and “date/time.” In some examples, ontology 760 is made up of many domains. Each domain shares one or more property nodes with one or more other domains. For example, the “date/time” property node is 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.

[0220] While FIG. 7C illustrates two example domains within ontology 760, other domains 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 is associated with a “send a message” actionable intent node, and further includes property nodes such as “recipient(s),” “message type,” and “message body.” The property node “recipient” is further defined, for example, by the sub-property nodes such as “recipient name” and “message address.”

[0221] In some examples, ontology 760 includes all the domains (and hence actionable intents) that the digital assistant is capable of understanding and acting upon. In some examples, ontology 760 is modified, such as by adding or removing entire domains or nodes, or by modifying relationships between the nodes within the ontology 760. [0222] In some examples, nodes associated with multiple related actionable intents are clustered under a “super domain” in ontology 760. For example, a “travel” super-domain includes a cluster of property nodes and actionable intent nodes related to travel. The actionable intent nodes related to travel includes “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) 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” share one or more of the property nodes “start location,” “destination,” “departure date/time,” “arrival date/time,” and “party size.”

[0223] In some examples, each node in ontology 760 is 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 are the so-called “vocabulary” associated with the node. The respective set of words and/or phrases associated with each node are 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” includes 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” includes words and phrases such as “call,” “phone,” “dial,” “ring,” “call this number,” “make a call to,” and so on. The vocabulary index 744 optionally includes words and phrases in different languages.

[0224] Natural language processing module 732 receives the candidate text representations (e.g., text string(s) or token sequence(s)) from STT processing module 730, and for each candidate representation, determines what nodes are implicated by the words in the candidate text representation. In some examples, if a word or phrase in the candidate text representation is found to be associated with one or more nodes in ontology 760 (via vocabulary index 744), the word or phrase “triggers” or “activates” those nodes. Based on the quantity and/or relative importance of the activated nodes, natural language processing module 732 selects 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 is selected. In some examples, the domain having the highest confidence value (e.g., based on the relative importance of its various triggered nodes) is selected. In some examples, the domain is 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.

[0225] User data 748 includes 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, natural language processing module 732 uses 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 is 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.

[0226] It should be recognized that in some examples, natural language processing module 732 is implemented using one or more machine learning mechanisms (e.g., neural networks). In particular, the one or more machine learning mechanisms are configured to receive a candidate text representation and contextual information associated with the candidate text representation. Based on the candidate text representation and the associated contextual information, the one or more machine learning mechanisms are configured to determine intent confidence scores over a set of candidate actionable intents. Natural language processing module 732 can select one or more candidate actionable intents from the set of candidate actionable intents based on the determined intent confidence scores. In some examples, an ontology (e.g., ontology 760) is also used to select the one or more candidate actionable intents from the set of candidate actionable intents.

[0227] Other details of searching an ontology based on a token string are described in U.S. Utility Application Serial No. 12/341,743 for “Method and Apparatus for Searching Using An Active Ontology,” filed December 22, 2008, the entire disclosure of which is incorporated herein by reference.

[0228] In some examples, once natural language processing module 732 identifies an actionable intent (or domain) based on the user request, natural language processing module 732 generates a structured query to represent the identified actionable intent. In some examples, the structured query includes 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 says “Make me a dinner reservation at a sushi place at 7.” In this case, natural language processing module 732 is 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 includes 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 using STT processing module 730, natural language processing module 732 generates a partial structured query for the restaurant reservation domain, where the partial structured query includes the parameters {Cuisine = “Sushi”} and {Time = “7pm”}. 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} are not specified in the structured query based on the information currently available. In some examples, natural language processing module 732 populates 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 populates a {location} parameter in the structured query with GPS coordinates from the user device.

[0229] In some examples, natural language processing module 732 identifies multiple candidate actionable intents for each candidate text representation received from STT processing module 730. Further, in some examples, a respective structured query (partial or complete) is generated for each identified candidate actionable intent. Natural language processing module 732 determines an intent confidence score for each candidate actionable intent and ranks the candidate actionable intents based on the intent confidence scores. In some examples, natural language processing module 732 passes the generated structured query (or queries), including any completed parameters, to task flow processing module 736 (“task flow processor”). In some examples, the structured query (or queries) for the m-best (e.g., m highest ranked) candidate actionable intents are provided to task flow processing module 736, where m is a predetermined integer greater than zero. In some examples, the structured query (or queries) for the m-best candidate actionable intents are provided to task flow processing module 736 with the corresponding candidate text representation(s). [0230] Other details of inferring a user intent based on multiple candidate actionable intents determined from multiple candidate text representations of a speech input are described in U S. Utility Application Serial No. 14/298,725 for “System and Method for Inferring User Intent From Speech Inputs,” filed June 6, 2014, the entire disclosure of which is incorporated herein by reference.

[0231] Task flow processing module 736 is configured to receive the structured query (or queries) from natural language 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 are provided in task flow models 754. In some examples, task flow models 754 include procedures for obtaining additional information from the user and task flows for performing actions associated with the actionable intent.

[0232] As described above, in order to complete a structured query, task flow processing module 736 needs to initiate additional dialogue with the user in order to obtain additional information, and/or disambiguate potentially ambiguous utterances. When such interactions are necessary, task flow processing module 736 invokes dialogue flow processing module 734 to engage in a dialogue with the user. In some examples, dialogue flow processing module 734 determines how (and/or when) to ask the user for the additional information and receives and processes the user responses. The questions are provided to and answers are received from the users through I/O processing module 728. In some examples, dialogue flow processing module 734 presents 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 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 generates 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 then populates 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.

[0233] Once task flow processing module 736 has completed the structured query for an actionable intent, task flow processing module 736 proceeds to perform the ultimate task associated with the actionable intent. Accordingly, task flow processing module 736 executes 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” includes 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 Cafe, date = 3/12/2012, time = 7pm, party size = 5}, task flow processing module 736 performs the steps of: (1) logging onto a server of the ABC Cafe 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.

[0234] In some examples, task flow processing module 736 employs 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 acts 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.). In some examples, the protocols and application programming interfaces (API) required by each service are specified by a respective service model among service models 756. Service processing module 738 accesses the appropriate service model for a service and generates requests for the service in accordance with the protocols and APIs required by the service according to the service model.

[0235] For example, if a restaurant has enabled an online reservation service, the restaurant submits 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 establishes a network connection with the online reservation service using the web address stored in the service model, and sends 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. [0236] In some examples, natural language processing module 732, dialogue flow processing module 734, and task flow processing module 736 are 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 is a dialogue response to the speech input that at least partially fulfills the user’s intent. Further, in some examples, the generated response is output as a speech output. In these examples, the generated response is sent to speech synthesis processing 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 is data content relevant to satisfying a user request in the speech input.

[0237] In examples where task flow processing module 736 receives multiple structured queries from natural language processing module 732, task flow processing module 736 initially processes the first structured query of the received structured queries to attempt to complete the first structured query and/or execute one or more tasks or actions represented by the first structured query. In some examples, the first structured query corresponds to the highest ranked actionable intent. In other examples, the first structured query is selected from the received structured queries based on a combination of the corresponding speech recognition confidence scores and the corresponding intent confidence scores. In some examples, if task flow processing module 736 encounters an error during processing of the first structured query (e.g., due to an inability to determine a necessary parameter), the task flow processing module 736 can proceed to select and process a second structured query of the received structured queries that corresponds to a lower ranked actionable intent. The second structured query is selected, for example, based on the speech recognition confidence score of the corresponding candidate text representation, the intent confidence score of the corresponding candidate actionable intent, a missing necessary parameter in the first structured query, or any combination thereof

[0238] Speech synthesis processing module 740 is configured to synthesize speech outputs for presentation to the user. Speech synthesis processing module 740 synthesizes speech outputs based on text provided by the digital assistant. For example, the generated dialogue response is in the form of a text string. Speech synthesis processing module 740 converts the text string to an audible speech output. Speech synthesis processing module 740 uses 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 processing module 740 is configured to synthesize individual words based on phonemic strings corresponding to the words. For example, a phonemic string is associated with a word in the generated dialogue response. The phonemic string is stored in metadata associated with the word. Speech synthesis processing module 740 is configured to directly process the phonemic string in the metadata to synthesize the word in speech form.

[0239] In some examples, instead of (or in addition to) using speech synthesis processing module 740, speech synthesis is performed on a remote device (e.g., the server system 108), and the synthesized speech is 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 is possible to obtain higher quality speech outputs than would be practical with client-side synthesis.

[0240] Additional details on digital assistants can be found in the U.S. Utility Application No. 12/987,982, entitled “Intelligent Automated Assistant,” filed January 10, 2011, and U.S. Utility Application No. 13/251,088, entitled “Generating and Processing Task Items That Represent Tasks to Perform,” filed September 30, 2011, the entire disclosures of which are incorporated herein by reference.

[0241] 4. Systems and Methods for Conversational and Environmental Transcriptions

[0242] With reference now to FIGS. 8A-8E and 9A-9B, exemplary techniques for transcriptions and transcription assistance are described.

[0243] With reference to FIG. 8A, generally, a conversation between a user and one or more other users may be initiated. The conversation may correspond to a voice communication (e g., telephone call), a video communication, a conversation through a social media platform, a conversation in a virtual and/or augmented reality setting, and the like. For example, a user of electronic device 800 may be engaged in a telephone conversation with other users, such as users corresponding to contact identifiers stored on electronic device 800 (e.g., contacts with names “Jessica,” “Tim,” “Mary,” and “John”). Electronic device 800 may correspond to a smart phone device, for example. While the conversation takes place, a textual representation (e.g., a transcription) of the conversation may obtained. In some examples, prior to initiating the conversation between the parties, participant identifiers may be identified, corresponding to participants to be included in the conversation (e g., participants included in conference call information, participants the user has entered to establish an outgoing call, etc ). In particular, a prompt requesting transcription approval may be provided to each participant of the conversation For example, the prompt may provide the participant with the option to include or exclude the respective participant’s inputs from being included in the textual representation obtained from the conversation. The prompt may also include various options related to the transcription of the conversation. For instance, the prompt may further provide the participant with the option to anonymize or otherwise modify the respective participant’s inputs, such that the obtained textual representation includes modified input from the respective participant. A modified textual representation of the conversation may include various modifications, such as anonymized user names (e.g., “User A: Hello ”) The modified textual representation may also omit various items of information, such as personal information (e.g., addresses, phone numbers, account numbers, and the like). A response to a provided prompt is then received from devices associated with the various participants, including responses that may approve transcription, deny transcription, or otherwise approve a modified version of transcription for the respective participant.

[0244] Initiation of the transcription may occur in various ways. For example, the user may indicate a desire to transcribe the conversation through various configurations or settings prior to the conversation being initiated and the transcription approval prompts being sent to the various users. The user may also provide an input during an already-established conversation, for example, by activating an affordance such as affordance 802 depicted on an active call screen. In some examples, affordance 802 may be used to toggle between the active call screen and the textual representation of the conversation (discussed in part via FIG. 8B), for example, when transcription has already been initiated. In some examples, initiation of the transcription may occur based on various context information. For instance, a transcription of a conversation may be initiated in response to a respective threshold being exceeded, such as a noise threshold (e.g., the user is engaged in a video call within a crowded supermarket). As another example, the transcription may be initiated in response to the detection of various trigger words or phrases. Specifically, one or more users participating in the conversation may utter a phrase such as “can you repeat that,” “say that again,” “what was that?” and the like. In some examples, the trigger word or phrase may correspond to an explicit request from the user of the electronic device to begin a transcription, such as “Start the transcription now.”

[0245] Generally, proactive and reactive assistance using the textual representation may be provided to users and may be based on various factors. Referring to FIG. 8B, in some examples, content associated with the conversation is identified based on the textual representation, wherein the content includes one or more inputs from the user of electronic device 800 and/or the other participants of the conversation. Such input may generally trigger reactive assistance from electronic device 800 (and/or other devices associated with the conversation) as described herein. In particular, the input may correspond to speech input, text input, input from activating various affordances, controlling one or more secondary devices, and the like. For example, the user may activate a mute button, share various media items within the conversation, control virtual objects in a virtual setting, etc. For example, speech input may be received from the various participants of the conversation, such as speech input from participant associated with contact named “Jessica,” including speech “Let’s talk about our 2020 performance overall.” The speech input may be processed using one or more STT processing modules in order to obtain a textual representation of the speech, such as textual representation 804 displayed on the display screen of electronic device 800. The textual representation may include additional information such as the participant name (e.g., identified using speech recognition and/or the telephone line and participant identifier), a time associated with the speech input, and the like. Additional textual representations may be obtained corresponding to other participants of the conversation, such as textual representation 806 including “Tim (10:45AM): Can we start with the financial report?” The textual representations may be obtained and displayed as the conversation takes place, for example, textual representations 804 and 806 may be displayed as the respective participants utter the corresponding speech within the conversation.

[0246] The input may also correspond to other various factors related to the user, digital assistant characteristics, environmental attributes, and the like. Whether such input is translated into a textual representation within the transcription may be subject pre-approval by a respective user as described herein. For example, using one or more sensors, cameras, proximity sensors, and the like, an input may be detected including characteristics related to user appearance, orientation, pose, and/or positioning. The input may include information regarding the attentive state of the user, as discussed in more detail herein. Such information may be related to user head pose, gaze direction, eye movements, lip movements, body movements (e.g., hands covering the user’s face), and the like. For instance, various movements such as sign language may be detected (e g., using one or more image recognition techniques) and translated into a representation which is provided as an output within the textual representation of the ongoing conversation, as described herein. A user named “John,” for example, may perform various hand motions (e g., a circular motion near the user’s chest) corresponding to the sign language representation for “Please.” Accordingly, upon detecting the hand motions coming from user “John,” the transcription may include a textual representation such as “John (signing): Please.”

[0247] Other content may also be identified, such as the orientation and position of a digital assistant representation. For example, the user may be communicating with other users using a smartphone or smart television, such that a digital assistant representation is displayed at various locations on a screen (e.g., an “Orb” in an upper comer of an associated television display). The appearance and orientation of the digital assistant representation may also be identified, such as whether the digital assistant is represented in an active state (e.g., a larger “orb” with swirling lights), a passive state (e.g., a smaller “orb”), an idle state, and the like. In some examples, the digital assistant representation may be displayed in the context of a virtual, augmented, or mixed reality environment (e.g., a digital assistant object depicted as “floating” in front of the user’s point of view). Environmental sounds may also be detected and translated into a textual representation within the transcription. For example, in response to a phone ringing in the environment of a conversation participant name “Mary,” the sound may be detected and characterized, resulting in the transcription “Mary (background): Phone ringing.”

[0248] Other environmental characteristics may also be detected and corresponding representations provided within the conversation transcription, such as room lighting, camera movement (e.g., background appearance changes), presences of other persons, animals, etc.

In some examples, objects within the environment may be detected and various text transcribed corresponding to the detected objects. The objects may correspond to virtual objects detected in a VR/AR environment, and/or physical objects detected in a physical environment. For example, during a video call on the user’s smartphone, a pet of the user may momentarily enter environmental area being captured by the camera, such that the pet is detected (e.g., via a scene graph as discussed further herein). Accordingly, a textual representation may be generated including “The cat sat on John’s lap.” As another example, in a co-presence session (e g., within an AR/VR environment), various objects or user avatars may move about the user’s viewing perspective, enter or exit the environment, etc. Based on these detected events, appropriate transcriptions may be made, as further discussed with respect to FIGS. 9A-9B.

[0249] As the textual representation of the conversation is being obtained, the textual representation may be stored in one or more memories of electronic device 800. The textual representation may also be stored with additional metadata corresponding to information regarding the conversation, such as participants, timing information, conversation topics, parameters identified from the conversation, and the like. In particular, with reference to textual representation 806, parameters may be identified such as the participant identifier “Tim,” the time associated with the corresponding utterance “10:45AM,” and various keywords uttered by the user, such as “financial report.” Additional metadata corresponding to keywords may also be stored with the textual representation. For example, “financial report” may be associated with metadata such as “finance,” “money,” “economics,” “accounting,” “reports,” and the like.

[0250] Referring to FIG. 8C, determination is made whether content associated with the conversation corresponds to predefined content. In general, the predefined content may correspond to content which would trigger actions related to transcription assistance, such as content indicating a user intent to review a portion of the textual representation, explicit questions from the users (e.g., “How many wins do the Lakers have again?”) content indicative of missing information (e.g., “I can’t find the 2019 Marketing Report ”), and the like. In particular, the user of electronic device 800 may provide an utterance 808 such as “Go back to the discussion on the financial report.” Using natural language processing and intent determination as discussed herein, for example based in part of the words “go back” or “go back to the discussion,” determination is made that the user would like to review portions of the textual representation. Based on the textual representation of the conversation, including corresponding metadata, determination is made that the user intent of the utterance corresponds to an intent to review portions of the conversation related to “financial reports” and optionally, portions of the textual representation including metadata associated with “finance,” “money,” “economics,” “accounting,” “reports,” and the like.

[0251] In some examples, in response to a determination that the content is not associated with predefined content, additional content associated with the conversation is identified. Alternatively, in response to a determination that the content is associated with predefined content, a portion of the textual representation is identified. For example, utterance 808 may be indicative of an intent to review portions of the textual representation directed to “finance” or “money” and in particular, “financial reports.” The textual representation may thus be analyzed based on the predefined content in order to locate portions of the textual representation which are relevant to the predefined content. In this example, a portion of the textual representation including information related to a “financial report” may be identified. In general, such identification may involve identifying a first instance of information related to the predefined content, and any subsequent instances of such information within predetermined ranges (e.g., any content including the same or similar content within a minute of the initially identified content). Here, for example, textual representation 806 (referring back to FIG. 8B) may be identified as a first instance of the textual representation including content related to a “financial report.” Accordingly, a relevant textual representation may be identified, which corresponds to the initially displayed textual representation 806, corresponding to utterance “Can we start with the financial report?” within the conversation.

[0252] The predefined content may be associated with names, topics, dates, events, locations or other information identified within the conversation based on keywords or other data detection mechanisms. Semantic matching and grouping of the content may also facilitate retrieval of the respective textual representation portions. For example, names of all attendees of a conversation may be identified and associated with keywords such as “this group,” “everyone,” and the like. Topics associated with the conversation may also be grouped or otherwise organized based on semantic similarity. For example, the conversation may include a general discussion on “recruiting,” including semantically relevant references to “interview,” “salary,” “offer,” and the like. Any semantically similar references may be grouped together (e.g., in a vector space), such that these references may be included within respective identified portions of an obtained textual representation based on inputs matching predefined content associated with “recruiting,” for example.

[0253] Referring to FIG. 8D, an output responsive to the respective input is provided based on the identified portion. In some examples, displayed textual representation 810 may include an indication, such as indication 812, that the textual representation corresponds to the predefined content identified from the conversation, such as utterance 208 depicted in FIG. 8C. Indication 810 may include the relevant textual representation “Tim (10:45AM): Can we start with the financial report?”, for example. Additional textual representations may include indicators or other affordances to enable the user to expand the respective textual representation, such as affordance 814. The displayed textual representations are not limited to those depicted in FIG. 8D and may be displayed or grouped in various ways, such as based on participants, times associated with respective inputs, in a single scrollable textual representation, and the like. The textual representations may also be provided to secondary device, such as a headset, laptop or desktop computer, smart watch, and the like.

[0254] In general, the user of electronic device 800 may also interact with a digital assistant of the device while the conversation is active. The interaction may include an input or other signal indicating an intent to communicate either publicly or privately with the digital assistant. For example, an intent to communicate publicly with the digital assistant may result in the user’s digital assistant request and/or the digital assistant response being provided within the conversation to be received by all participating parties. In contrast, an intent to communicate privately with the digital assistant may result in the user’s digital assistant request and/or digital assistant response being provided only to the requesting user. The intent to communicate either privately or publicly may be conveyed by utilizing a specific input (e.g., pressing a physical button on the device or a specific displayed affordance) or by providing a specific speech input (e.g., “Respond to all with the score of the Lakers game”). The intent may also be determined by a user preference, such as a default preference that any digital assistant request provided during a communication session be private unless indicated otherwise. The response may include a displayed response, and may further include an audible response based on the displayed response (e.g., the audible response may be output while reducing the volume of the corresponding communication session).

[0255] User input may also be associated with an intent to obtain information associated with content of the conversation, which may trigger proactive assistance using the textual representation of the conversation. In particular, the user input may include an interrogatory sentence having a reference to a parameter, such as “Does anyone know how Corporation ABC stock is doing today?” The user input may be part of the conversation and may not be directed to a digital assistant of the device. In this example, “Corporation ABC stock” may be identified as a respective parameter based on natural language processing. In some examples, the referenced parameter is utilized in order to retrieve an identifier associated with one or more of a website, a document, a media file (e.g., photo, video), etc. A search query may also be initiated using at least the referenced parameter (e.g., an internet search for “Corporation ABC stock”). An output responsive to such a query may then be provided within the conversation, or alternatively, as a result separate from the conversation (e.g., a notification including a current stock price for “Corporation ABC”).

[0256] Referring to FIG. 8E, a representation 816 of the conversation may generally be provided once the user is no longer a participant within the conversation. In particular, in response to detecting an end to the conversation (e.g., all participants withdraw from the conversation) and/or when the user of electronic device 800 withdraws from the conversation (e.g., the user activates an “end call” affordance), a participant representation is obtained for each participant of the conversation. The participant representations may correspond to any participants who were present for at least a portion of the conversation. Various other metadata associated with the conversation may be obtained in order to provide the representation of the conversation. For example, timing information may be obtained, such as when participants joined and left the conversation, the conversation duration, the date of the conversation, the start and end times of the conversation, etc. Information associated with conversation topics may also be obtained. The representation of the conversation may include shorts descriptions of the topics, and/or may include relevant paraphrases and literal quotes from the textual representation (e.g., a quote identifying the participant speaker).

[0257] In some examples, the obtained textual representation of the conversation is stored in memory only temporarily. For example, in response to detecting an end to the conversation and/or when the user of electronic device 800 withdraws from the conversation, the textual representation corresponding to the conversation is stored in memory. At a later time (e.g., a predetermined time after the detection and storage), the textual representation is removed from memory. The user and/or conversation participants may also configure various settings associated with timing and removal of the textual representation from memory.

[0258] In general, proactive assistance using the textual representation may be provided based on various environmental conditions and detected user states. For instance, the attentive state of the user may be utilized in order to identify relevant portions of the textual representation. Information associated with the attentive state of the user may be identified, for example, in order to determine whether the attentive state of the user corresponds to a predefined state. To the extent the attentive state of the user does not correspond to any predefined state, the system may continue to identify additional information associated with the attentive state of the user. The predefined state may generally correspond to a state of distraction, tiredness, boredom, or other state indicative that the user may not have recognized or not fully recognized a portion of the conversation. In general, a gaze associated with the user may be determined, such as whether the user is looking at the display of a respective device, whether the user is looking at a specific object displayed on the device (e.g., a displayed textual representation for the conversation), and the like. As described further herein, user eye activity and head movement activity may also be used to determine attentive state.

[0259] In general, a conversation may take place within a virtual or augmented reality setting including one or more conversation participants, such that information associated with the general environment of the electronic device is obtained. A direction of the user gaze may be determined, for example, in the context of the virtual or augmented reality system.

For example, the presence of one or more conversation participants and/or avatars associated with conversation participants within a virtual setting may be detected. Determination may further be made whether the user gaze is directed towards one of the conversation participants and/or avatars associated with the conversation participants, and/or whether the user is uttering speech while gazing at the respective participants and/or avatars. To the extent the user gaze is directed towards one of the conversation participants and/or avatars associated with the conversation participants, the attentive state of the user may be determined to be focused on the conversation and thus not correspond to the predefined state. Alternatively, to the extent the user gaze is not directed towards one of the conversation participants and/or avatars associated with the conversation participants (e.g., directed to other objects, other detected persons and/or avatars of persons not associated with the conversation), the attentive state of the user may be determined to be distracted and thus correspond to the predefined state. In some examples, detection of the user’s body position, hand movements, or other personal characteristics indicative of attentive state may be determined. For example, detection may be made that the user slouching (or alternatively, sitting up straight, etc.), and further engaging in acts such as eye rubbing, yawning, and the like. In this example, determination may be made, based on predefined states (e.g., a known body movement or body position) that the user is tired, distracted, etc.

[0260] Information related to a user’ s eye movements and head movements may also be utilized to determine the user’s attentive state. In particular, a user’s eye closure amount may be detected within a predetermined time during a conversation. For example, a user’s eyes may be monitored for a several second range to determine whether the user’s eyes are open, closed, partially open or closed, etc. To the extent the user’s eyes are determined to be closed for greater than a threshold amount of time within the predetermined time (e.g., eyes closed for more than seven seconds within a ten second range), determination is made that the user’s attentive state corresponds to a lack of focus, and thus corresponds to the predefined state. In some examples, movement of the user’s head position may be compared to predefined movement (e.g., a user nodding their head consistent with tiredness). To the extent the movement of the user’s head position corresponds to the predefined movement, determination is made that the user’s attentive state corresponds to tired and/or distracted, and thus corresponds to the predefined state.

[0261] In some examples, a user’s heart rate may be monitored, for example, via a secondary device such as a smart watch. To the extent the user’s heart rate falls below a threshold rate, determination may be made that the user’s attentive state corresponds to a state such as tired or otherwise disengaged. To the extent the user’s heart rate is detected above a specific threshold rate, determination may be made that the user is engaged or otherwise excited and/or alert. Voice characteristics of the user may also be monitored to determine attentive state, such as by monitoring prosody information (e.g., stress, intonation, pitch, speech, etc.) in order to determine whether the user is distracted or otherwise disengaged. For example, to the extent the user is talking at a high volume with a high stress level, determination may be made that the user’s attentive state corresponds to irritable, frustrated, etc.

[0262] Other predefined states may be detected, such that information may be utilized to determine whether the attentive state of the user corresponds such predefined states. In particular, the predefined state in some examples may correspond to a state of inquiry regarding objects in an environment related to an ongoing conversation. In some examples, various objects within a setting may be related to a respective conversation. In particular, conversation taking place in the context of a virtual or augmented reality setting may include various avatars corresponding to conversation participants, and various virtual objects populated as the conversation takes place. For example, a conversation participant may cause a virtual car to be populated in the virtual environment while telling a story about the virtual car object. For instance, while placing the virtual car in the environment, the conversation participant may utter “Here is my 2008 Tesla Roadster.” The user of the electronic device may later utter, while gazing in the direction of the virtual car object, “What type of car is this again?” In accordance with a determination, based on the user gaze, that the referenced “car” from the utterance corresponds to the virtual car object related to the ongoing conversation, determination is made that the attentive state corresponds to a predefined state.

[0263] In some examples, in accordance with a determination that user’s attentive state corresponds to a predefined state, a portion of a textual representation of the respective conversation is identified based on a time corresponding to the identified information associated with the user’s attentive state. For example, in accordance with a determination that an amount of time associated with the user’s eye closure exceeds the predetermined threshold amount of time, a respective portion of the textual representation is identified corresponding to a time related to the user’s eye closure. For instance, detection is made that the user closed their eyes shortly after the beginning of a discussion regarding a specific topic (e.g., “marketing”). The portion of the textual representation corresponding to the beginning of the “marketing” discussion may be identified based on timing information related to the initial detection of eye closure and subsequently detected prolonged eye closure.

Accordingly, an output may be provided to the user based on the identified portion, such as a brief summary of the “marketing” discussion (e g., “John discussed marketing for about three minutes”). In some examples, a prompt may be provided, such as a prompt including the text “Would you like to review the discussion regarding marketing?” The user may respond to the prompt, and the relevant portion of the textual representation may then be displayed.

[0264] Generally, a transcription may be generated based on a variety of contexts, such as conversational context. The conversational context may be related to a phone call as described with respect to FIGS. 8A-8E. In some examples, an environmental context may also be utilized in order to generate the transcription. The environmental context may include a conversational context between users, and/or may include environmental factors such as environmental appearance, noise, object movement, weather, location, and the like. The environmental context may be detected based on a variety of electronic devices, such as a head-mounted display used in an extended reality (XR) setting, for example. The head- mounted display may be coupled to one or more cameras and may include an opaque display for displaying virtual and real objects (e.g., for providing video of the physical environment to the user, with potential virtual objects superimposed, etc ). In some examples, the head- mounted display may include an additive display, such that the physical setting may be viewed directly through the display, with virtual objects displayed directly on the additive display. [0265] With reference to FIG. 9A, a representation 900 of a setting corresponding to an environment of an electronic device is depicted. In some examples, the representation may correspond to an XR setting, and may include representations of one or more virtual objects and/or virtual environmental features, and one or more physical objects and/or physical environmental features. In some examples, the XR setting may include representations of solely virtual features (e g., an “all virtual” environment) or all physical features (e g , an “all physical” environment). In general, the XR setting may be generated by way of a scene graph including a set of identifiers associated with the representation of the setting. In particular, the set of identifiers may represent information used in order to convey and otherwise render the setting for proper viewing by the user via the head-mounted display. As an example, representation 900 may be associated with a physical environment of the user, such as a living room. The set of identifiers may generally define various objects associated with a respective environment. In this example, representation 900 may include a door representation 902 and a window representation 904. Accordingly, the set of identifiers may include a description of a first identifier for “door” and a description of a second identifier for “window.” The set of identifiers may further define a relationship between the first identifier and the second identifier, which includes “to the right of.” In particular, the relationship may define that “window” representation 904 is depicted as “to the right of’ “door” representation 902. The relationships may be defined from the perspective of the user wearing the head- mounted display, for example. Thus, representation 900 may be rendered to the user based at least in part on the scene graph including a set of identifiers.

[0266] In some examples, a first textual representation 906 (e.g., a transcription) may be provided based at least in part on the set of identifiers. In particular, the set of identifiers may include additional contextual information associated with representation 900, such weather information, location information, audio information, and the like. For example, representation 900 may correspond to the user’s living room which is physically located in the city of Atlanta, GA. Accordingly, a current location of the electronic device is retrieved, and first textual representation 906 is provided as including the current location.

Furthermore, weather information corresponding to the current location may also be obtained, such as “sunny, 70 degrees.” A respective textual representation may be obtained based on at least the location information and/or the weather information (e.g., a paraphrase), such as “warm and sunny day in Atlanta.” Accordingly, first textual representation 906 may be populated with the respective textual representation, such as “It’s a warm and sunny day in Atlanta.”

[0267] Various users may be associated with representation 900, such as a second user corresponding to representation 908. Representation 908 may correspond to the representation of a physical user (e.g., as viewed through an additive display or display on an opaque display), or may correspond to a solely virtual representation such as an avatar controlled by the second user. In other examples, representation 908 may correspond to a virtual character (e.g., a character not controlled by a human user). An identity associated with representation 308 may be obtained in various ways. For example, a representation corresponding to a physical user may be identified by way of facial recognition (e.g., utilizing a photo application on the device), such that the representation is identified as corresponding to a user recognized on the device via various photos stored on the device. In some examples, a representation corresponding to a virtual user may be identified by way of contact information (e.g., utilizing a contacts application on the device). In particular, representation 900 may correspond to a XR session including one or more virtual participants, such that the representation is identified as corresponding to a user recognized from the session participant information (e.g., participant identifiers, contact numbers, IP addresses, etc.). Here, representation 908 may be identified as corresponding to a user named “Jim,” based on a photos application and/or contacts application for example. In some examples, users within the context of representation 900 may utter various speech input. For example, the second user associated with representation 908 may utter “Will Maeve be here soon?”

[0268] With reference to FIG. 9B, an event associated with representation 900 may be detected, such as a third user entering the environment. Accordingly, an updated set of identifiers may be retrieved based on the detected event. For example, a physical user may arrive at the location represented by representation 900, such as by walking through door 902 depicted within representation 900. Alternatively, a user may enter the virtual session (e.g., using call-in or log-in information), such that an avatar associated with the user is displayed within representation 900. Here, a representation 910, associated with a third user, may be displayed based on the third user entering the environment. Accordingly, an updated set of identifiers may be retrieved, which may include an identifier and corresponding description associated with the new third user corresponding to representation 910. For example, the third user associated with representation 910 may correspond to a contact, within an address book of the user, named “Maeve ”

[0269] In general, detecting an event associated with the representation of the setting may include detecting various events or other occurrences. For example, various virtual or physical objects within the field of view of the user may move about the environment, such that the updated set of identifiers include at least one identifier indicative of the movement (e.g., a representation for “door” 902 may include description information for “open,” “closed,” “opening,” “closing,” etc.). Various new objects may also move into the field of view of the user, such that the updated set of identifiers include at least one identifier indicative new object (e.g., a new identifier with a description of an object such as “sun,” “clouds,” etc.).

[0270] In some examples, a determination is made whether the updated set of identifiers satisfies a predetermined criterion. Specifically, the predetermined criterion may be used in order to determine whether to add information to the transcription based on the updated set of identifiers. For example, the determination that the updated set of identifiers satisfies a predefined criterion may include at least one of the identified movement corresponding to a predefined movement, such as an object that is moving quickly through the environment (e.g., transcribe information for a baseball being hit across a field, as opposed to a cloud slowly moving across the sky). The determination that the updated set of identifiers satisfies a predefined criterion may further include a determination whether the object associated with the identified movement corresponding to a predefined object (e.g., transcribing information for a large truck obscuring the field of view, as opposed to the hands of a clock). Various other types of criterion may be used which are indicative of whether to include respective information within the transcription. For example, in a large group of people, the criterion may specify to only transcribe information corresponding to known contacts of a user. When in a moving vehicle, for example, the criterion may specify to only transcribe information related to events occurring within the vehicle, and only a small number of events occurring outside the vehicle (e.g., landmarks being passed by the vehicle, other vehicle within certain proximity of the vehicle, etc.)

[0271] In accordance with a determination that the updated set of identifiers satisfy a predefined criterion, the first textual representation is modified based on the updated set of identifiers. The modified first textual representation is then provided to the user (e.g., displayed and/or audibly provided at the device). For example, as discussed above with reference to FIG. 9A, the speech input “Will Maeve be here soon?” may be detected from second user associated with representation 908. The predefined criterion may specify to transcribe any events related to speech input from other users associated with the environment (or to transcribe such events unless the environment includes a large amount of users, etc.). Accordingly, first textual representation 906 is modified to include the text “Jim asks ‘Will Maeve be here soon?’” As discussed with reference to FIG. 9B, representation 910 may correspond to a contact within an address book of the user named “Maeve.” The predefined criterion may specify to transcribe any events related to contacts within the address book of the user. Accordingly, first textual representation 906 is modified to include the text “Maeve arrives.” The predefined criterion may also include specific speech content that is or is not to be included in the transcription (e g., explicit/vulgar content, etc.). Other detected media content (e g., movies, music) may be defined by the predefined criterions, for example, to be included within the transcription (e.g., “Satisfaction by the Rolling Stones played in the background ”). Such content may be generally included unless explicit/vulgar, may be included only to the extent the detected media is consistent with the user’s media preferences, and the like.

[0272] As discussed in the context of FIGS. 8A-8E, proactive and reactive assistance may be provided using the transcription. In particular, an input may be received from a user of the electronic device, and a user intent may be further determined based on the input. In some examples, in accordance with a determination that the determined intent corresponds to an intent to review at least a specific portion of the first textual representation, the first textual representation is provided as including the specific portion. For example, the user may utter the phrase “what time did Maeve get here”? As discussed with respect to FIGS. 8A-8E, the textual representation may then be analyzed based on user query in order to locate portions of the textual representation which are relevant to the query. In this example, a portion of the textual representation including information related to a “Maeve” reference may be identified. In general, such identification may involve identifying a first instance of information related to the predefined content, and any subsequent instances of such information within predetermined ranges (e.g., any content including the same or similar content within a minute of the initially identified content). Here, a time stamp associated with the text entry “Maeve arrives,” may be returned to the user, such as “Maeve arrived at 10:00AM.” [0273] In some examples, in accordance with a determination that the updated set of identifiers does not satisfy a predefined criterion, a “background” transcription may still be continually updated. In particular, a second textual representation may be modified based on the updated set of identifiers, such that the modified textual representation is stored for potential future retrieval. As an example, the user may begin using the device when the weather is sunny, without any clouds in the sky. During the course of using the device, clouds may begin to appear (e.g., through window 904 depicted in representation 900). The cloud appearing may not be associated with the satisfaction of any predefined criterion. However, a transcription may be included within the second textual representation including “It starts to become cloudy outside” (e.g., the transcription is stored but not provided to the user). Accordingly, in response to a user query “when did it get cloudy outside?”, the second textual representation may be utilized in order to, for example, obtain a timestamp associated with the cloudy weather in order to respond to the user query. The user may also retrieve the entire second textual representation for review, may retrieve select portions of the second textual representation, and the like.

[0274] Various privacy controls may also be utilized by users of the transcription system in order to protect personal information. In general, user preferences may define which content should be included in a given transcription, and which content should not be included in a given transcription. An input may be received from the user, for example, to share a respective transcription with another user (e.g., first textual representation 906). In response to the input, a user preference associated with sharing transcriptions is obtained. The user preference may define, for example, to not include (or to anonymize) specific information, such as any information related to specific contacts defined by the user (e.g., the user’s children). In accordance with a determination that the user preferences include predefined preferences, the first textual representation is adjusted, and the adjusted textual representation is then provided to the third party. For example, the transcription may include a conversation between the user and the user’s child, such as “John (parent): What time does your class end today?; Jacob (child): We end at 3PM.” In response to the user requesting to share the transcription with another user, at least a portion of the textual representation is adjusted prior to sending the textual representation to another user, in accordance with the user preferences. For example, the respective transcription portion may only include the user’s speech transcription (but not the child’s speech transcription), may simply include “[Conversation omitted],” or may include no information at all. To the extent the user preferences do not include any conditions relevant to the respective transcription to be provided to a third party, the unadjusted textual representation may be provided in its entirety.

[0275] In some examples, transcriptions from multiple users may be shared and combined into a single transcription, subject to privacy settings. In particular, a second textual representation may be received from a third party, and a third textual representation may be obtained based on the first textual representation and the second textual representation. For instance, multiple users may attend a concert or other live event together, such that each user utilizes the same or similar device (e.g., a head mounted display). The perspective-specific content may be detected and provided via a transcription at each user device, such that the resulting transcriptions are aggregated together in order to provide a multi-perspective transcription of the event. Various portions of the transcriptions may be combined such that those portions of the transcription are not duplicated within the transcription (e.g., the resulting transcription may only include a single reference to a song playing, even though each transcription includes the same reference).

[0276] FIG. 10 illustrates process 1000 for transcription assistance according to various examples. At block 1002, a textual representation of a conversation between a user and at least one conversation participant is obtained. In some examples, prior to initiating the conversation between the user and the at least one conversation participant, a plurality of participants associated with the conversation are identified, the plurality of participants including the user and the at least one conversation participant. In some examples, a prompt requesting transcription approval is provided to each participant of the plurality of participants. In some examples, a response to a provided prompt is received from a first respective participant of the plurality of participants. In some examples, in accordance with a determination that the response includes a transcription approval, the textual representation of the conversation between the user and the at least one conversation participant is obtained, wherein the textual representation includes input from the first respective participant. In some examples, a response to a provided prompt is receive from a second respective participant of the plurality of participants. In some examples, in accordance with a determination that the response includes a transcription denial, the textual representation of the conversation between the user and the at least one conversation participant is obtained, wherein the textual representation does not include input from the second respective participant. In some examples, a response to a provided prompt is received from a third respective participant of the plurality of participants. In some examples, in accordance with a determination that the response includes a modified transcription approval, a respective textual representation of input received from the third respective participant is obtained. In some examples, the respective textual representation is modified based on the modified transcription approval, wherein the obtained textual representation of the conversation between the user and the at least one conversation participant includes the modified textual representation.

[0277] At block 1004, content associated with the conversation is identified based on the textual representation, wherein the content includes at least one of a first input from the user and a second input from the at least one conversation participant. In some examples, an intent is determined based on at least the first input from the user and the second input from the at least one conversation participant. In some examples, in accordance with a determination that the intent corresponds to an intent to review at least a portion of the textual representation of the conversation, determination is made that the content is associated with predefined content, wherein the identified portion of the textual representation corresponds to the specific portion. In some examples, while the conversation is active, an input directed to the digital assistant is received from the user, and an output responsive to the input is provided to the user. In some examples, providing, to the user, an output responsive to the input directed to a digital assistant includes, in accordance with a determination that the input directed to the digital assistant is associated with an intent to communicate privately, forgoing providing the input within the conversation and providing the responsive output to the user without providing the responsive output within the conversation, and, in accordance with a determination that the input directed to the digital assistant is not associated with an intent to communicate privately, providing the input within the conversation and providing, within the conversation, the responsive output to the user.

[0278] At block 1006, determination is made whether the content is associated with predefined content At block 1008, in response to a determination that the content is not associated with predefined content, additional content associated with the conversation is identified. At block 1010, in response to a determination that the content is associated with predefined content, a portion of the textual representation is identified based on the content.

In some examples, a name is identified from the first input from the user, and in accordance with a determination that the identified name corresponds to a participant of the conversation, determination is made that the content is associated with predefined content. In some examples, at least one input, from the participant corresponding to the identified name, is identified within the textual representation. In some examples, the identified at least one input, from the participant corresponding to the identified name, is provided as the responsive output. In some examples, at least one topic included within the content associated with the conversation is identified based on the textual representation. In some examples, a referenced topic is identified from the first input from the user, and in accordance with a determination that the at least one identified topic corresponds to the referenced topic, determination is made that the content is associated with predefined content. In some examples, the portion of the textual representation including input corresponding to at least one identified topic is identified. In some examples, the identified portion including the input is provided as the responsive output.

[0279] At block 1012, an output responsive to at least one of the first input and the second input is provided based on the identified portion. In some examples, a user intent corresponding to a respective user input within the content is identified from the content, and in accordance with a determination that the user intent corresponds to a request to obtain information associated with the content, information is retrieved to satisfy the request. In some examples, determination is made that the user intent corresponds to a request to obtain information associated with the content by identifying, within the respective user input, an interrogatory sentence, and a reference to a parameter within the content associated with the conversation. In some examples, retrieving information to satisfy the request includes identifying, within the respective user input, a reference to a parameter within the content associated with the conversation, and retrieving an identifier associated with at least one of a website, a document, and a media file. In some examples, retrieving information to satisfy the request includes initiating a search query associated with the request to obtain information, and providing a result responsive to the search query. In some examples, in response to detecting at least one of an end to the conversation and the user withdrawing from the conversation, a participant representation is obtained for each participant of the conversation. In some examples, at least one topic corresponding to the conversation is identified, and a representation of the conversation is provided including the obtained participant representations and the identified at least one topic. In some examples, at least one of an end to the conversation and the user withdrawing from the conversation is detected at a first time. In some examples, in response to the detection, the obtained textual representation is stored in memory, and at a time corresponding to a predetermined time after the first time, the stored textual representation is removed from the memory. [0280] FIG. 11 illustrates process 1100 for transcription assistance according to various examples. At block 1102, a textual representation of a conversation between a user and at least one conversation participant is obtained. In some examples, prior to initiating the conversation between the user and the at least one conversation participant, a plurality of participants associated with the conversation is identified, the plurality of participants including the user and the at least one conversation participant. In some examples, a prompt requesting transcription approval is provided to each participant of the plurality of participants. In some examples, in response to detecting at least one of an end to the conversation and the user withdrawing from the conversation, a participant representation is obtained for each participant of the conversation, at least one topic corresponding to the conversation is identified, and a representation of the conversation including the obtained participant representation and the identified at least one topic is provided.

[0281] At block 1104, information associated with an attentive state of the user is identified. In some examples, identifying information associated with an attentive state of the user includes detecting a gaze associated with the user, wherein the gaze is associated with a gaze direction, and determining whether the gaze direction is directed at a displayed object associated with the conversation. In some examples, while the conversation is active, an input directed to a digital assistant is received from the user, and an output responsive to the input is provided to the user. In some examples, providing, to the user, an output responsive to the input directed to a digital assistant includes, in accordance with a determination that the input directed to the digital assistant is associated with an intent to communicate privately, forgoing providing the input within the conversation and providing the responsive output to the user without providing the responsive output within the conversation, and in accordance with a determination that the input directed to the digital assistant is not associated with an intent to communicate privately, providing the input within the conversation and providing, within the conversation, the responsive output to the user. In some examples, identifying information associated with an attentive state of the user includes detecting an object, wherein the detected object corresponds to one of a virtual object or physical object, receiving speech input from the user, and determining whether the received speech input includes a reference to the detected object. By allowing digital assistant interactions during an ongoing conversation, the system enhances device functionality by providing digital assistant responses to at least some of the users of the ongoing conversation. Leveraging in conversation digital assistant interactions makes the device more efficient by eliminating the need for users to open different applications or web browsers on-device to conduct such queries, thus conserving system resources. Thus, these features reduce power usage and improve battery life of the device by enabling the user to use the device more quickly and efficiently.

[0282] At block 1106, determination is made whether the attentive state corresponds to a predefined state. In some examples, information associated with an environment of the electronic device is obtained, and in accordance with a determination that the information corresponds to predefined information, determination is made that the attentive state of the user corresponds to a predefined state. In some examples, the information is obtained by detecting presence of at least one of a conversation participant and an avatar associated with a conversation participant. In some examples, information associated with an attentive state of the user is identified by detecting a user gaze directed towards at least one of the conversation participant and the avatar associated with the conversation participant. In some examples, the information obtained by detecting at least one of speech, received from the user, directed to at least one of a conversation participant and an avatar associated with a conversation participant, and speech, directed to the user, from at least one of a conversation participant and an avatar associated with a conversation participant. In some examples, determining that the information corresponds to predefined information includes, for a predetermined duration of time, determining whether a user gaze is directed towards at least one of a conversation participant and an avatar associated with the conversation participant. In some examples, determining that the information corresponds to predefined information includes, for a predetermined duration of time, detecting an exchange of speech between the user at least one of a conversation participant and an avatar associated with a conversation participant. By providing assistance based on environmental factors and user gaze, the system enhances device functionality by facilitating quick navigation in response to user actions related to a conversation. Such navigation makes the device more efficient by eliminating the need for users to search through the transcription manually, thus conserving system resources. Thus, these features reduce power usage and improve battery life of the device by enabling the user to use the device more quickly and efficiently.

[0283] At block 1108, in accordance with a determination that the attentive state does not correspond to a predefined state, additional information associated with the attentive state of the user is identified. At block 1110, in accordance with a determination that the attentive state corresponds to a predefined state, a portion of the textual representation is identified based on a time corresponding to the identified information. In some examples, identifying information associated with an attentive state of the user includes detecting, within a predetermined time, at least one event corresponding to eye closure, identifying an amount of time corresponding to the detected at least one event corresponding to eye closure, and determining whether the identified amount of time exceeds a predetermined threshold amount of time. In some examples, identifying a portion of the textual representation based on a time corresponding to the identified information includes, in accordance with a determination that the identified amount of time exceeds the predetermined threshold amount of time, identifying, based on the predetermined time, a respective portion of the textual representation as the identified portion. In some examples, identifying information associated with an attentive state of the user includes detecting movement of a head position associated with the user, and determining whether the movement of the head position corresponds to a predefined movement. In some examples, identifying a portion of the textual representation based on a time corresponding to the identified information includes, in accordance with a determination that the movement of the head position corresponds to the predefined movement, identifying, based on the movement of the head position, a respective portion of the textual representation as the identified portion. By providing assistance based on eye closure and head movements, the system enhances device functionality by facilitating quick navigation in response to potentially involuntary user actions during a conversation. Such navigation makes the device more efficient by eliminating the need for user to later navigate and search through the transcription manually to find missed information, thus conserving system resources. Thus, these features reduce power usage and improve battery life of the device by enabling the user to use the device more quickly and efficiently.

[0284] At block 1112, an output is provided to the user based on the identified portion.

In some examples, providing, based on the identified portion, an output to the user includes providing a prompt based on the identified information, receiving an input from the user responsive to the prompt, and providing the identified portion of the textual representation based on the input. In some examples, at least one of an end to the conversation and the user withdrawing from the conversation is detected at a first time. In some examples, in response to the detection, the obtained textual representation of the conversation is stored in memory, and at a time corresponding to a predetermined time after the first time, the stored textual representation is removed from the memory. By removing the transcription from memory after a predetermined time, the system enhances device functionality by making memory available for new transcriptions to be stored. This memory allocation also makes the device more efficient by freeing memory space for other device functions, thus conserving system resources. Thus, these features reduce power usage and improve battery life of the device by enabling the user to use the device more quickly and efficiently.

[0285] FIGS. 12A-12B illustrate process 1200 for transcription assistance according to various examples. With reference to FIG. 12A, at block 1202, a representation of a setting corresponding to an environment of the electronic device is obtained. At block 1204, a set of identifiers associated with the representation of the setting is retrieved. At block 1206, a first textual representation based on the set of identifiers is provided. In some examples, providing a first textual representation based on the set of identifiers includes retrieving, for each identifier of the set of identifiers, at least one description, retrieving at least one relationship from the set of identifiers, and providing the first textual representation as including the at least one description and the at least one relationship. In some examples, a current location of the electronic device is retrieved, and the first textual representation is provided as including the current location. In some examples, weather information associated with a current location is retrieved, a respective textual representation is obtained corresponding to the weather information, and the first textual representation is provided as including the respective textual representation. In some examples, an avatar representation is identified from the representation of the setting, and contact information associated with the electronic device is retrieved. In some examples, an identity associated with the avatar representation is identified from the contact information, and the first textual representation is provided as including the identity. In some examples, a person is detected from the representation of the setting, and contact information associated with the electronic device is retrieved. In some examples, an identity associated with the person is identified from the contact information, and the first textual representation is provided as including the identity.

[0286] At block 1208, an event associated with the representation of the setting is detected. At step 1210, an updated set of identifiers is retrieved based on the detected event. In some examples, detecting an event associated with the representation of the setting includes identifying movement associated with an object within a field of view corresponding to the electronic device, wherein the updated set of identifiers include at least one identifier indicative of the movement. In some examples, detecting an event associated with the representation of the setting includes detecting a new object moving into a field of view corresponding to the electronic device, wherein the updated set of identifiers include at least one identifier indicative of the new object.

[0287] With reference to FIG. 6B, at step 1212, a determination is made whether the updated set of identifiers satisfies a predetermined criterion. In some examples, the determination that the updated set of identifiers satisfies a predefined criterion includes at least one of the identified movement corresponding to a predefined movement and the object associated with the identified movement corresponding to a predefined object. In some examples, the determination that the updated set of identifiers satisfies a predefined criterion includes at least one of an identified movement of the new object corresponding to a predefined movement and the new object corresponding to a predefined.

[0288] At step 1214, in accordance with a determination that the updated set of identifiers does not satisfy a predefined criterion, events associated with the representation of the setting continue to be detected. At step 1216, in accordance with a determination that the updated set of identifiers satisfy a predefined criterion, the first textual representation is modified based on the updated set of identifiers. In some examples, speech is detected as the detected event associated with the representation of the setting, wherein the determination that the updated set of identifiers satisfies a predetermined criterion includes the detected speech corresponding to at least one of speech from a predefined entity and predefined speech content. In some examples, playing media is detected as the detected event associated with the representation of the setting, wherein the determination that the updated set of identifiers satisfies a predefined criterion includes the detected playing media corresponding to the predefined media. In some examples, a second textual representation is received from a third party, and a third textual representation is obtained based on the first textual representation and the second textual representation, wherein the third textual representation includes at least a portion of the first textual representation and at least a portions of the second textual representation.

[0289] At step 1218, the modified first textual representation is provided. In some examples, an input is received from a user of the electronic device and a user intent is determined based on the input. In some examples, in accordance with a determination that the determined intent corresponds to an intent to review at least a specific portion of the first textual representation, the first textual representation is provided as including the specific portion. In some examples, in accordance with a determination that the updated set of identifiers does not satisfy a predefined criterion, a second textual representation is modified based on the updated set of identifiers, and the modified textual representation is stored, wherein the second textual representation includes the first textual representation. In some examples, an input is received from a user of the electronic device, wherein the input is associated with the first textual representation. In some examples, a user preference corresponding to textual representation of content is retrieved, and information associated with the first textual representation is provided, based on the user preference, to a third party. In some examples, in accordance with a determination that the user preferences include predefined preferences, the first textual representation is adjusted, and the adjusted textual representation is provided to the third party. In some examples, in accordance with a determination that the user preferences do not include predefined preferences, the first textual representation is provided to the third party.

[0290] In accordance with some implementations, a computer-readable storage medium (e.g., a non-transitory computer readable storage medium) is provided, the computer-readable storage medium storing one or more programs for execution by one or more processors of an electronic device, the one or more programs including instructions for performing any of the methods or processes described herein.

[0291] In accordance with some implementations, an electronic device (e.g., a portable electronic device) is provided that comprises means for performing any of the methods or processes described herein.

[0292] In accordance with some implementations, an electronic device (e.g., a portable electronic device) is provided that comprises a processing unit configured to perform any of the methods or processes described herein.

[0293] In accordance with some implementations, an electronic device (e.g., a portable electronic device) is provided that comprises one or more processors and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for performing any of the methods or processes described herein.

[0294] 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.

[0295] 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.

[0296] As described above, one aspect of the present technology is the gathering and use of data available from various sources to improve transcriptions and transcription assistance. 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, twitter IDs, home addresses, data or records relating to a user’s health or level of fitness (e.g., vital signs measurements, medication information, exercise information), date of birth, or any other identifying or personal information.

[0297] 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 enhance the accuracy of transcription assistance.

Accordingly, use of such personal information data enables users to calculated control of transcription and transcription assistance. Further, other uses for personal information data that benefit the user are also contemplated by the present disclosure. For instance, health and fitness data may be used to provide insights into a user’s general wellness, or may be used as positive feedback to individuals using technology to pursue wellness goals.

[0298] The present disclosure 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. Such policies should be easily accessible by users, and should be updated as the collection and/or use of data changes. 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/sharing should occur after receiving the informed consent of the users. Additionally, such entities should consider taking 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. In addition, policies and practices should be adapted for the particular types of personal information data being collected and/or accessed and adapted to applicable laws and standards, including jurisdiction-specific considerations. For instance, in the US, collection of or access to certain health data may be governed by federal and/or state laws, such as the Health Insurance Portability and Accountability Act (HIPAA); whereas health data in other countries may be subject to other regulations and policies and should be handled accordingly. Hence different privacy practices should be maintained for different personal data types in each country.

[0299] Despite the foregoing, the present disclosure also contemplates examples 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 transcription assistance, 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 or anytime thereafter. In another example, users can select not to certain information, such as contact information, for transcription assistance. In yet another example, users can select to limit the length of time environment-specific data is maintained or entirely prohibit certain environment-specific data from being gathered. In addition to providing “opt in” and “opt out” options, the present disclosure contemplates providing notifications relating to the access or use of personal information. For instance, a user may be notified upon downloading an app that their personal information data will be accessed and then reminded again just before personal information data is accessed by the app.

[0300] Moreover, it is the intent of the present disclosure that personal information data should be managed and handled in a way to minimize risks of unintentional or unauthorized access or use. Risk can be minimized by limiting the collection of data and deleting data once it is no longer needed. In addition, and when applicable, including in certain health related applications, data de-identifi cation can be used to protect a user’s privacy. De- identification may be facilitated, when appropriate, by removing specific identifiers (e.g., date of birth, etc.), controlling the amount or specificity of data stored (e.g., collecting location data a city level rather than at an address level), controlling how data is stored (e.g., aggregating data across users), and/or other methods.

[0301] Therefore, although the present disclosure broadly covers use of personal information data to implement one or more various disclosed examples, the present disclosure also contemplates that the various examples can also be implemented without the need for accessing such personal information data. That is, the various examples 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 system for transcription assistance, or publicly available information.

Claims

CLAIMS What is claimed is:

1. A computer-implemented method, comprising: at an electronic device with one or more processors and a memory: obtaining a textual representation of a conversation between a user and at least one conversation participant; identifying, based on the textual representation, content associated with the conversation, wherein the content includes at least one of a first input from the user and a second input from the at least one conversation participant; in response to a determination that the content is associated with predefined content: identifying, based on the content, a portion of the textual representation; and providing, based on the identified portion, an output responsive to at least one of the first input and the second input.

2. The method of claim 1, comprising: prior to initiating the conversation between the user and the at least one conversation participant: identifying a plurality of participants associated with the conversation, the plurality of participants including the user and the at least one conversation participant; and providing, to each participant of the plurality of participants, a prompt requesting transcription approval.

3. The method of claim 2, comprising: receiving, from a first respective participant of the plurality of participants, a response to a provided prompt; and in accordance with a determination that the response includes a transcription approval: obtaining the textual representation of the conversation between the user and the at least one conversation participant, wherein the textual representation includes input from the first respective participant.

4. The method of claim 2, comprising: receiving, from a second respective participant of the plurality of participants, a response to a provided prompt; and in accordance with a determination that the response includes a transcription denial: obtaining the textual representation of the conversation between the user and the at least one conversation participant, wherein the textual representation does not include input from the second respective participant.

5. The method of claim 2, comprising: receiving, from a third respective participant of the plurality of participants, a response to a provided prompt; and in accordance with a determination that the response includes a modified transcription approval: obtaining a respective textual representation of input received from the third respective participant; and modifying the respective textual representation based on the modified transcription approval, wherein the obtained textual representation of the conversation between the user and the at least one conversation participant includes the modified textual representation.

6. The method of any one of claims 1-5, comprising: determining, based on at least the first input from the user and the second input from the at least one conversation participant, a user intent; and in accordance with a determination that the user intent corresponds to an intent to review at least a specific portion of the textual representation of the conversation, determining that the content is associated with predefined content, wherein the identified portion of the textual representation corresponds to the specific portion.

7. The method of any one of claims 1-6, comprising: identifying, from the first input from the user, a name; and in accordance with a determination that the identified name corresponds to a participant of the conversation, determining that the content is associated with predefined content.

8. The method of claim 7, comprising: identifying at least one input, within the textual representation, from the participant corresponding to the identified name; and providing, as the responsive output, the identified at least one input from the participant corresponding to the identified name.

9. The method of any one of claims 1-8, comprising: identifying, based on the textual representation, at least one topic included within the content associated with the conversation; identifying, from the first input from the user, a referenced topic; and in accordance with a determination that the at least one identified topic corresponds to the referenced topic, determining that the content is associated with predefined content.

10. The method of claim 9, comprising: identifying the portion of the textual representation including input corresponding to at least one identified topic; and providing, as the responsive output, the identified portion including the input.

11. The method of any one of claims 1-10, comprising: identifying, from the content, a user intent corresponding to a respective user input within the content; and in accordance with a determination that the user intent corresponds to a request to obtain information associated with the content, retrieving information to satisfy the request.

12. The method of claim 11, comprising: determining that the user intent corresponds to a request to obtain information associated with the content by identifying, within the respective user input: an interrogatory sentence; and a reference to a parameter within the content associated with the conversation.

13. The method of claim 11, wherein retrieving information to satisfy the request comprises: identifying, within the respective user input, a reference to a parameter within the content associated with the conversation; and retrieving an identifier associated with at least one of a website, a document, and a media file.

14. The method of claim 11, wherein retrieving information to satisfy the request comprises: initiating a search query associated with the request to obtain information; and providing a result responsive to the search query.

15. The method of any one of claims 1-14, comprising: while the conversation is active: receiving, from the user, an input directed to a digital assistant; and providing, to the user, an output responsive to the input directed to a digital assistant.

16. The method of claim 15, wherein providing, to the user, an output responsive to the input directed to a digital assistant comprises: in accordance with a determination that the input directed to the digital assistant is associated with an intent to communicate privately: forgoing providing the input within the conversation; and providing the responsive output to the user without providing the responsive output within the conversation; and in accordance with a determination that the input directed to the digital assistant is not associated with an intent to communicate privately: providing the input within the conversation; and providing, within the conversation, the responsive output to the user.

17. The method of any one of claims 1-16, comprising: in response to detecting at least one of an end to the conversation and the user withdrawing from the conversation: obtaining, for each participant of the conversation, a participant representation; identifying at least one topic corresponding to the conversation; and providing a representation of the conversation including the obtained participant representations and the identified at least one topic.

18. The method of any one of claims 1-17, comprising: detecting, at a first time, at least one of an end to the conversation and the user withdrawing from the conversation; in response to the detection: storing, in the memory, the obtained textual representation of the conversation; and at a time corresponding to a predetermined time after the first time, removing the stored textual representation from the memory.

19. An electronic device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions which cause the electronic device to: obtain a textual representation of a conversation between a user and at least one conversation participant; identify, based on the textual representation, content associated with the conversation, wherein the content includes at least one of a first input from the user and a second input from the at least one conversation participant; in response to a determination that the content is associated with predefined content: identify, based on the content, a portion of the textual representation; and provide, based on the identified portion, an output responsive to at least one of the first input and the second input.

20. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to: obtain a textual representation of a conversation between a user and at least one conversation participant; identify, based on the textual representation, content associated with the conversation, wherein the content includes at least one of a first input from the user and a second input from the at least one conversation participant; in response to a determination that the content is associated with predefined content: identify, based on the content, a portion of the textual representation; and provide, based on the identified portion, an output responsive to at least one of the first input and the second input.

21. An electronic device, comprising: means for obtaining a textual representation of a conversation between a user and at least one conversation participant; means for identifying, based on the textual representation, content associated with the conversation, wherein the content includes at least one of a first input from the user and a second input from the at least one conversation participant; means for, in response to a determination that the content is associated with predefined content, identifying, based on the content, a portion of the textual representation; and means for providing, based on the identified portion, an output responsive to at least one of the first input and the second input.

22. An electronic device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing the methods of any one of claims 1- 18.

23. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to perform the methods of any one of claims 1-18.

24. An electronic device, comprising: means for performing the methods of any one of claims 1-18.

25. A computer-implemented method, comprising: at an electronic device with one or more processors and a memory: obtaining a textual representation of a conversation between a user and at least one conversation participant; identifying information associated with an attentive state of the user; in accordance with a determination that the attentive state corresponds to a predefined state: identifying a portion of the textual representation based on a time corresponding to the identified information; and providing, based on the identified portion, an output to the user.

26. The method of claim 25, comprising: prior to initiating the conversation between the user and the at least one conversation participant: identifying a plurality of participants associated with the conversation, the plurality of participants including the user and the at least one conversation participant; and providing, to each participant of the plurality of participants, a prompt requesting transcription approval.

27. The method of any one of claims 25-26, wherein identifying information associated with an attentive state of the user comprises: detecting a gaze associated with the user, wherein the gaze is associated with a gaze direction; and determining whether the gaze direction is directed at a displayed object associated with the conversation.

28. The method of any one of claims 25-27, wherein identifying information associated with an attentive state of the user comprises: detecting, within a predetermined time, at least one event corresponding to eye closure; identifying an amount of time corresponding to the detected at least one event corresponding to eye closure; and determining whether the identified amount of time exceeds a predetermined threshold amount of time.

29. The method of claim 28, wherein identifying a portion of the textual representation based on a time corresponding to the identified information comprises: in accordance with a determination that the identified amount of time exceeds the predetermined threshold amount of time: identifying, based on the predetermined time, a respective portion of the textual representation as the identified portion.

30. The method of any one of claims 25-29, wherein identifying information associated with an attentive state of the user comprises: detecting movement of a head position associated with the user; and determining whether the movement of the head position corresponds to a predefined movement.

31. The method of claim 30, wherein identifying a portion of the textual representation based on a time corresponding to the identified information comprises: in accordance with a determination that the movement of the head position corresponds to the predefined movement: identifying, based on the movement of the head position, a respective portion of the textual representation as the identified portion.

32. The method of any one of claims 25-31, wherein providing, based on the identified portion, an output to the user comprises: providing a prompt based on the identified information; receiving an input from the user responsive to the prompt; and providing the identified portion of the textual representation based on the input.

33. The method of any one of claims 25-32, comprising: obtaining information associated with an environment of the electronic device; in accordance with a determination that the information corresponds to predefined information, determining that the attentive state of the user corresponds to a predefined state.

34. The method of claim 33, comprising: obtaining the information by detecting presence of at least one of a conversation participant and an avatar associated with a conversation participant; and identifying information associated with an attentive state of the user by detecting a user gaze directed towards at least one of a conversation participant and the avatar associated with a conversation participant.

35. The method of claim 33, comprising: obtaining the information by detecting at least one of: speech, received from the user, directed to at least one of a conversation participant and an avatar associated with a conversation participant, and speech, directed to the user, from at least one of a conversation participant and an avatar associated with a conversation participant.

36. The method of claim 33, wherein determining that the information corresponds to predefined information comprises: for a predetermined duration of time: determining whether a user gaze is directed towards at least one of a conversation participant and an avatar associated with a conversation participant.

37. The method of claim 33, wherein determining that the information corresponds to predefined information comprises: for a predetermined duration of time: detecting an exchange of speech between the user at least one of a conversation participant and an avatar associated with a conversation participant.

38. The method of any one of claims 25-37, wherein identifying information associated with an attentive state of the user comprises: detecting an object, wherein the detected object corresponds to one of a virtual object or physical object; receiving speech input from the user; and determining whether the received speech input includes a reference to the detected object.

39. The method of any one of claims 25-38, comprising: while the conversation is active: receiving, from the user, an input directed to a digital assistant; and providing, to the user, an output responsive to the input directed to a digital assistant.

40. The method of claim 39, wherein providing, to the user, an output responsive to the input directed to a digital assistant comprises: in accordance with a determination that the input directed to the digital assistant is associated with an intent to communicate privately: forgoing providing the input within the conversation; and providing the responsive output to the user without providing the responsive output within the conversation; and in accordance with a determination that the input directed to the digital assistant is not associated with an intent to communicate privately: providing the input within the conversation; and providing, within the conversation, the responsive output to the user.

41. The method of any one of claims 25-40, comprising: in response to detecting at least one of an end to the conversation and the user withdrawing from the conversation: obtaining, for each participant of the conversation, a participant representation; identifying at least one topic corresponding to the conversation; and providing a representation of the conversation including the obtained participant representations and the identified at least one topic.

42. The method of any one of claims 25-41, comprising: detecting, at a first time, at least one of an end to the conversation and the user withdrawing from the conversation; in response to the detection: storing, in the memory, the obtained textual representation of the conversation; and at a time corresponding to a predetermined time after the first time, removing the stored textual representation from the memory.

43. An electronic device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions which cause the electronic device to: obtain a textual representation of a conversation between a user and at least one conversation participant; identify information associated with an attentive state of the user; in accordance with a determination that the attentive state corresponds to a predefined state: identify a portion of the textual representation based on a time corresponding to the identified information; and provide, based on the identified portion, an output to the user.

44. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to: obtain a textual representation of a conversation between a user and at least one conversation participant; identify information associated with an attentive state of the user; in accordance with a determination that the attentive state corresponds to a predefined state: identify a portion of the textual representation based on a time corresponding to the identified information; and provide, based on the identified portion, an output to the user.

45. An electronic device, comprising: means for obtaining a textual representation of a conversation between a user and at least one conversation participant; means for identifying information associated with an attentive state of the user; means for, in accordance with a determination that the attentive state corresponds to a predefined state, identifying a portion of the textual representation based on a time corresponding to the identified information; and means for providing, based on the identified portion, an output to the user.

46. An electronic device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing the methods of any one of claims 25- 42.

47. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to perform the methods of any one of claims 25-42.

48. An electronic device, comprising: means for performing the methods of any one of claims 25-42.

49. A computer-implemented method, comprising: at an electronic device with one or more processors and memory: obtaining a representation of a setting corresponding to an environment of the electronic device; retrieving a set of identifiers associated with the representation of the setting; providing a first textual representation based on the set of identifiers; detecting an event associated with the representation of the setting; retrieving, based on the detected event, an updated set of identifiers; in accordance with a determination that the updated set of identifiers satisfies a predefined criterion: modifying the first textual representation based on the updated set of identifiers; and providing the modified first textual representation.

50. The method of claim 49, wherein providing a first textual representation based on the set of identifiers comprises: retrieving, for each identifier of the set of identifiers, at least one description; retrieving at least one relationship from the set of identifiers; and providing the first textual representation as including the at least one description and the at least one relationship.

51. The method of any one of claims 49-50, wherein detecting an event associated with the representation of the setting comprises: identifying movement associated with an object within a field of view corresponding to the electronic device, wherein the updated set of identifiers include at least one identifier indicative of the movement.

52. The method of claim 51, wherein the determination that the updated set of identifiers satisfies a predefined criterion includes at least one of: the identified movement corresponding to a predefined movement, and the object associated with the identified movement corresponding to a predefined object.

53. The method of any one of claims 49-52, wherein detecting an event associated with the representation of the setting comprises: detecting a new object moving into a field of view corresponding to the electronic device, wherein the updated set of identifiers include at least one identifier indicative of the new object.

54. The method of claim 53, wherein the determination that the updated set of identifiers satisfies a predefined criterion includes at least one of: an identified movement of the new object corresponding to a predefined movement, and the new object corresponding to a predefined object.

55. The method of any one of claims 49-54, comprising: retrieving a current location of the electronic device; and providing the first textual representation as including the current location

56. The method of any one of claims 49-55, comprising: retrieving weather information associated with a current location of the electronic device; obtaining a respective textual representation corresponding to the weather information; and providing the first textual representation as including the respective textual representation.

57. The method of any one of claims 49-56, comprising: identifying an avatar representation from the representation of the setting; retrieving contact information associated with the electronic device; identifying, from the contact information, an identity associated with the avatar representation; and providing the first textual representation as including the identity.

58. The method of any one of claims 49-57, comprising: detecting a person from the representation of the setting; retrieving contact information associated with the electronic device; identifying, from the contact information, an identity associated with the person; and providing the first textual representation as including the identity.

59. The method of any one of claims 49-58, comprising: detecting speech as the detected event associated with the representation of the setting, wherein the determination that the updated set of identifiers satisfies a predefined criterion includes: the detected speech corresponding to at least one of speech from a predefined entity and predefined speech content.

60. The method of any one of claims 49-59, comprising: detecting playing media as the detected event associated with the representation of the setting, wherein the determination that the updated set of identifiers satisfies a predefined criterion includes the detected playing media corresponding to predefined media.

61. The method of any one of claims 49-60, comprising: receiving an input from a user of the electronic device; determining a user intent based on the input; and in accordance with a determination that the determined intent corresponds to an intent to review at least a specific portion of the first textual representation, providing the first textual representation including the specific portion.

62. The method of any one of claims 49-61, comprising: in accordance with a determination that the updated set of identifiers does not satisfy a predefined criterion: modifying a second textual representation based on the updated set of identifiers; and storing the modified textual representation, wherein the second textual representation includes the first textual representation.

63. The method of any one of claims 49-62, comprising: receiving an input from a user of the electronic device; determining a user intent based on the input; and in accordance with a determination that the determined intent corresponds to an intent to review at least a specific portion of the second textual representation, providing the second textual representation including the specific portion.

64. The method of any one of claims 49-63, comprising: receiving an input from a user of the electronic device, wherein the input is associated with the first textual representation; retrieving a user preference corresponding to textual representation content; and providing, based on the user preference, information associated with the first textual representation to a third party.

65. The method of claim 64, comprising: in accordance with a determination that the user preference includes predefined preferences: adjusting the first textual representation; and providing the adjusted textual representation to the third party in accordance with a determination that the user preferences do not include predefined preferences: providing the first textual representation to the third party.

66. The method of any one of claims 49-65, comprising: receiving, from a third party, a second textual representation; and obtaining a third textual representation based on the first textual representation and the second textual representation, wherein the third textual representation includes at least a portion of the first textual representation and at least a portions of the second textual representation.

67. An electronic device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions which cause the electronic device to: obtain a representation of a setting corresponding to an environment of the electronic device; retrieve a set of identifiers associated with the representation of the setting; provide a first textual representation based on the set of identifiers; detect an event associated with the representation of the setting; retrieve, based on the detected event, an updated set of identifiers; in accordance with a determination that the updated set of identifiers satisfies a predefined criterion: modify the first textual representation based on the updated set of identifiers; and provide the modified first textual representation.

68. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to: obtain a representation of a setting corresponding to an environment of the electronic device; retrieve a set of identifiers associated with the representation of the setting; provide a first textual representation based on the set of identifiers; detect an event associated with the representation of the setting; retrieve, based on the detected event, an updated set of identifiers; in accordance with a determination that the updated set of identifiers satisfies a predefined criterion: modify the first textual representation based on the updated set of identifiers; and provide the modified first textual representation.

69. An electronic device, comprising: means for obtaining a representation of a setting corresponding to an environment of the electronic device; means for retrieving a set of identifiers associated with the representation of the setting; means for providing a first textual representation based on the set of identifiers; means for detecting an event associated with the representation of the setting; means for retrieving, based on the detected event, an updated set of identifiers; means for, in accordance with a determination that the updated set of identifiers satisfies a predefined criterion, modifying the first textual representation based on the updated set of identifiers; and means for providing the modified first textual representation.

70. An electronic device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing the methods of any one of claims 49- 66

71. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to perform the methods of any one of claims 49-66.

72. An electronic device, comprising: means for performing the methods of any one of claims 49-66.