EP2691876A2 - Personnalisation de requêtes, de conversations et de recherches - Google Patents
Personnalisation de requêtes, de conversations et de recherchesInfo
- Publication number
- EP2691876A2 EP2691876A2 EP20120765100 EP12765100A EP2691876A2 EP 2691876 A2 EP2691876 A2 EP 2691876A2 EP 20120765100 EP20120765100 EP 20120765100 EP 12765100 A EP12765100 A EP 12765100A EP 2691876 A2 EP2691876 A2 EP 2691876A2
- Authority
- EP
- European Patent Office
- Prior art keywords
- user
- phrase
- action
- ontology
- agent action
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/332—Query formulation
- G06F16/3329—Natural language query formulation or dialogue systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/9032—Query formulation
- G06F16/90332—Natural language query formulation or dialogue systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/26—Speech to text systems
Definitions
- An augmented conversational understanding architecture may provide a mechanism for personalizing queries, conversations and searches.
- personal assistant programs and/or search engines often require specialized formatting and syntax. For example, a user's query of "I want to go see 'Inception' around 7" may be ineffective at communicating the user's true intentions when provided to a conventional system.
- Such systems may generally be incapable of deriving the context that the user is referring to a movie, and that the user desires results informing them of local theatres showing that movie around 7:00.
- Personalization of user interactions may be provided.
- a plurality of semantic concepts associated with the user may be loaded. If the phrase is determined to comprise at least one of the plurality of semantic concepts associated with the user, a first action may be performed according to the phrase. If the phrase is determined not to comprise at least one of the plurality of semantic concepts associated with the user, a second action may be performed according to the phrase.
- FIG. 1 is a block diagram of an operating environment
- FIG. 2 is a flow chart of a method for providing an augmented reality
- FIGs. 3A-3B are illustrations of example ontologies.
- FIG. 4 is a block diagram of a system including a computing device.
- a cloud (e.g., network storage-based) based service may allow for user personalization of searches, queries or instructions to a personal assistant (e.g., a software program).
- a personal assistant e.g., a software program.
- the ability to personalize such queries or instructions may be provided by rule driven techniques in conjunction with various ontologies and using the search terms, instruction statements and the user contexts to provide more accurate search or query results.
- Natural language speech recognition applications may allow for personalization of searches and actions. Components may focus on the user experience and/or provide a personalization engine, such as via components of a SDS.
- a user experience component may be available as part of a web search application via a browser running on a general purpose desktop or laptop computer or a specialized computing device such as a smart phone or a information kiosk in a mall.
- a personalization engine component may store various ontologies, iterate through a query to identify a user's intent, and attempt to match a semantic representation of the query to a particular ontology. For example, ABC Company may populate a shared ontology that may define semantic concepts such as creating an appointment.
- the semantic concept may be associated with attributes such as calendar servers, scheduling services, and synonyms (e.g., the term "S+" may be defined as a shortcut synonym for setting up a meeting). If the user is an employee of ABC Co., the term S+ ("S plus") may be inherited from the shared ontology and recognized as a shortcut to setting up an appointment using Outlook®.
- the personalization engine may also use additional user contexts (e.g., location, or previous state information) to merge additional shared ontologies.
- Other examples of personalization may comprise the user asking for "John Hardy's”; because the user is originally from Minnesota, the SDS may retrieve this information from the user's personal ontology (derived from profile, usage history, and other sources such as contacts and messaging content) and know that the user is looking for the BBQ restaurant located in Rochester, MN. If the user refers to "Rangers” the SDS may be able to infer, based on the personal ontology, that the user intends "NY Rangers” since they are a hockey fan. If the user were known to be a baseball fan, the user's intent may be interpreted as referring instead to the "Texas Rangers.” Such intent deciphering may be in combination with contextual information such as the time of year, what teams are playing that day, etc.
- a Spoken Language Understanding (SLU) component may receive a spoken or written conversation between users and/or a single-user originating query.
- the SLU may parse the words of a voice or text conversation and select certain items which may be used to fill out an XML data frame for particular contexts. For example, a restaurant context may have certain slots such as "type of food”, “location/address”, “outdoor dining”, “reservations required”, “hours open”, “day of week”, “time”, “number of persons”, etc.
- the SLU may attempt to fill different context data frames with both the parsed words from the conversation or query, and with other external information, such as GPS location information.
- the SLU may keep state during the conversation and fill the slots over the course of the conversation. For example, if user 1 says “How about tonight” and user 2 says “Saturday is better", the SLU may initially fill tonight in the day of the week slot and then fill Saturday in the day of the week slot. If a certain number of the slots in a particular context frame are filled, the SLU may infer that the context is correct and estimate the user intention. The SLU may also prompt the user for more information related to the intent. The SLU may then provide options to the user based on the determined user intent.
- FIG. 1 is a block diagram of an operating environment 100 comprising a spoken dialog system (SDS) 1 10.
- SDS 1 10 may comprise assorted computing and/or software modules such as a personal assistant program 112, a dialog manager 114, an ontology database 1 16, and/or a search agent 118.
- SDS 110 may receive queries and/or action requests from users over network 120. Such queries may be transmitted, for example, from a first user device 130 and/or a second user device 135 such as a computer and/or cellular phone.
- Network 120 may comprise, for example, a private network, a cellular data network, and/or a public network such as the Internet. Consistent with embodiments of the invention, SDS 110 may be operative to monitor conversations between first user device 130 and second user device 135.
- the primary component that drives the SDS may comprise dialog manager 114.
- This component may manage the dialog-based conversation with the user.
- Dialog manager 114 may determine the intention of the user through a combination of multiple sources of input, such as speech recognition and natural language understanding component outputs, context from the prior dialog turns, user context, and/or results returned from a knowledge base (e.g., search engine). After determining the intention, dialog manager 114 may take an action, such as displaying the final results to the user and/or continuing in a dialog with the user to satisfy their intent.
- FIG. 2 is a flow chart setting forth the general stages involved in a method
- Method 200 may be implemented using a computing device 400 as described in more detail below with respect to FIG. 4. Ways to implement the stages of method 200 will be described in greater detail below.
- Method 200 may begin at starting block 205 and proceed to stage 210 where computing device 400 may identify a plurality of users associated with a conversation.
- SDS 1 10 may monitor a conversation between a first user of first user device 130 and a second user of second user device 135.
- the first user and second user may be identified, for example, via an authenticated sign-in with SDS 110 and/or via identifying software and/or hardware IDs associated with their respective devices.
- Method 200 may then advance to stage 215 where computing device 400 may merge a plurality of ontologies.
- SDS 110 may load an ontology associated with the first user and the second user from ontology database 1 16.
- Each of the plurality of ontologies may comprise a plurality of semantic concepts and/or attributes associated with characteristics of at least one of the users, such as a workplace associated a user, a contacts database, a calendar, a previous action, a previous communication made by and/or between the users, a context, and/or a profile.
- the merger may comprise merging either and/or both users' ontologies with a shared/global ontology.
- a search engine may provide a shared ontology comprising data gathered and synthesized across many users, while a network application may publish an ontology comprising attributes associated with publicly available applications.
- a shared ontology may also be associated with an organization and may comprise attributes common to multiple employees. Merging one ontology with another may comprise, for example, creating associations between common terms, adding synonyms to a node, adding additional attribute nodes, sub nodes, and/or branches, and/or adding connections between nodes.
- Method 200 may then advance to stage 220 where computing device 400 may receive a natural language phrase from a user.
- SDS 110 may receive a phrase spoken and/or typed by the user into first user device 130.
- Method 200 may then advance to stage 225 where computing device 400 may load a model associated with a spoken dialog system.
- SDS 110 may load a language dictionary associated with the user's preferred spoken language.
- Method 200 may then advance to stage 230 where computing device 400 may translate the natural language phrase into an agent action.
- the phrase may be scanned for concepts that correlate to a search domain and/or an executable action associated with a network application. Words such as "dinner tonight" may scan to a "restaurant" search domain associated with a search action.
- Each domain may be associated with a plurality of slots that may comprise attributes for defining the scope of the action. For example, a restaurant domain may comprise slots for party size, type of cuisine, time, whether outdoor seating is available, etc. Dialog manager 114 may attempt to fill these slots based on the natural language phrase.
- Method 200 may then advance to stage 235 where computing device 400 may determine whether the recognition is acceptable. For example, dialog manager 114 may be unable to fill enough slots to provide a complete action, and/or additional phrases may be received from the initial user and/or another user involved in the conversation that modify the agent action prior to execution.
- method 200 may advance to stage 240 where computing device 400 may receive an update to the agent action.
- dialog manager may create a restaurant domain agent action for making a reservation.
- dialog manager may return to stage 230 to translate the new input and update the action accordingly.
- method 200 may advance to stage 245 where computing device 400 may perform the action.
- dialog manager 114 may create a lunch appointment calendar event.
- Method 200 may then advance to stage 250 where computing device 400 may display at least one result associated with the performed action to at least one of the plurality of users. For example, SDS 1 10 may populate the created lunch appointment to calendars associated with each of the first user and second user and/or display a confirmation that the event was created on their respective user devices. Method 200 may then end at stage 255.
- FIG. 3A is an illustration of a shared ontology 300.
- An ontology may generally comprise a plurality of semantic relationships between concept nodes.
- Each concept node may comprise a generalized grouping, an abstract idea, and/or a mental symbol and that node's associated attributes.
- one concept may comprise a person associated with attributes such as name, job function, home location, etc.
- the ontology may comprise, for example, a semantic relationship between the person concept and a job concept connected by the person's job function attribute.
- Shared ontology 300 may comprise a plurality of concept nodes 310(A)-(F). Each of the concept nodes may be associated with attribute nodes.
- person concept node 310(C) may be associated with a plurality of attributes 315(A)-(D). Attributes may be further associated with sub-nodes, such as where contact info attribute node 315(B) is associated with a plurality of sub-nodes 320(A)-(C). Similarly, attribute nodes may be associated with synonyms, such as where name attribute node 315(A) is associated with a nicknames synonym 325.
- Concept nodes 310(A)-(F) may be interconnected via a plurality of semantic relationships 330(A)-(B). For example, person attribute 310(C) may be connected to location attribute 310(F) via work semantic relationship 330(A) and/or home semantic relationship 330(B).
- FIG. 3B is an illustration of a personal ontology 350 comprising a user concept node 360.
- User concept node 360 may comprise a plurality of attribute nodes 370(A)-(D) associated with user details such as preferences, activities, relationships, and/or previous choices.
- User concept node 360 may comprise a semantic connection 375 associated with another concept node, such as a second user node 380 associated with a child of the user.
- An embodiment consistent with the invention may comprise a system for providing a context-aware environment.
- the system may comprise a memory storage and a processing unit coupled to the memory storage.
- the processing unit may be operative to receive a phrase from a user, load an ontology associated with the user, determine whether the phrase comprises at least one semantic concept associated with the ontology, and, if not, perform a first action according to the phrase.
- the processing unit may be operative to perform a second action according to the phrase.
- the phrase may comprise a spoken natural language phrase and the processing unit may be operative to convert the spoken phrase to a text-based phrase.
- the natural language phrase may comprise a typed phrase.
- the ontology may comprise, for example, terms and/or concepts associated with the user's workplace, previous actions, learned phrasing, slang, contact-derived references (e.g., "Billy-boy” equates to a contact named Bill Smith, Jr.), and/or previous communications.
- Another embodiment consistent with the invention may comprise a system for providing a personalized user interaction.
- the system may comprise a memory storage and a processing unit coupled to the memory storage.
- the processing unit may be operative to receive a phrase from a user, load an ontology associated with the user, translate the received phrase into an agent action, determine whether the phrase comprises at least one of the semantic concepts associated with the ontology, and, if so, modify the agent action, perform the modified agent action, and display at least one result associated with the performed agent action to the user.
- the agent action may comprise, for example, a search query, and being operative to modify the action may comprise the processing unit being operative to add a term to the query and/or replace a term of the query with a synonym.
- the agent action may comprise performing a task within an application, wherein an attribute associated with the ontology comprises a shortcut synonym associated with a semantic concept of performing the task within the application (e.g., a spoken command "exit" may be translated into application tasks of saving all open files and quitting the application).
- the context associated with the user may comprise, for example, a location of the user, a time the phrase was received, and a date the phrase was received.
- the received phrase may be associated with a conversation between the user and at least one second user.
- the processing unit may then be operative to receive a second phrase from the second user, load a second ontology associated with the second user, merge the two users' ontologies, translate the second received phrase into a second agent action, determine whether the second phrase comprises a semantic concept associated with the merged ontologies, and, if so, modify the agent action, perform the modified agent action, and display at least one result associated with the performed agent action to the second user.
- Yet another embodiment consistent with the invention may comprise a system for providing a context-aware environment.
- the system may comprise a memory storage and a processing unit coupled to the memory storage.
- the processing unit may be operative to identify a plurality of users associated with a conversation, merge a plurality of ontologies, each associated with one of the users, receive a first natural language phrase from a first user of the plurality of users, translate the natural language phrase into an agent action, and determine whether the agent action is associated with at least one of the semantic concepts associated with the merged ontologies.
- the processing unit may be operative to modify the agent action.
- the processing unit may then be operative to receive a second natural language phrase from a second user of the plurality of users, and determine whether the second natural language phrase is associated with the agent action. If so, the processing unit may be operative to update the agent action according to the second natural language phrase. The processing unit may then be operative to perform the agent action and display at least one result associated with the performed agent action to at least one of the plurality of users.
- FIG. 4 is a block diagram of a system including computing device 400.
- the aforementioned memory storage and processing unit may be implemented in a computing device, such as computing device 400 of FIG. 4. Any suitable combination of hardware, software, or firmware may be used to implement the memory storage and processing unit.
- the memory storage and processing unit may be implemented with computing device 400 or any of other computing devices 418, in combination with computing device 400.
- the aforementioned system, device, and processors are examples and other systems, devices, and processors may comprise the aforementioned memory storage and processing unit, consistent with embodiments of the invention.
- computing device 400 may comprise operating environment 100 as described above. System 100 may operate in other environments and is not limited to computing device 400.
- a system consistent with an embodiment of the invention may include a computing device, such as computing device 400.
- computing device 400 may include at least one processing unit 402 and a system memory 404.
- system memory 404 may comprise, but is not limited to, volatile (e.g., random access memory (RAM)), non- volatile (e.g., read-only memory (ROM)), flash memory, or any combination.
- System memory 404 may include operating system 405, one or more programming modules 406, and may include personal assistant program 1 12. Operating system 405, for example, may be suitable for controlling computing device 400's operation.
- embodiments of the invention may be practiced in conjunction with a graphics library, other operating systems, or any other application program and is not limited to any particular application or system. This basic configuration is illustrated in FIG. 4 by those components within a dashed line 408.
- Computing device 400 may have additional features or functionality.
- computing device 400 may also include additional data storage devices (removable and/or non-removable) such as, for example, magnetic disks, optical disks, or tape.
- additional storage is illustrated in FIG. 4 by a removable storage 409 and a non-removable storage 410.
- Computer storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data.
- System memory 404, removable storage 409, and non-removable storage 410 are all computer storage media examples (i.e., memory storage.)
- Computer storage media may include, but is not limited to, RAM, ROM, electrically erasable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store information and which can be accessed by computing device 400. Any such computer storage media may be part of device 400.
- Computing device 400 may also have input device(s) 412 such as a keyboard, a mouse, a pen, a sound input device, a touch input device, etc.
- Output device(s) 414 such as a display, speakers, a printer, etc. may also be included. The aforementioned devices are examples and others may be used.
- Computing device 400 may also contain a communication connection 416 that may allow device 400 to communicate with other computing devices 418, such as over a network in a distributed computing environment, for example, an Intranet or the Internet.
- Communication connection 416 is one example of communication media.
- Communication media may typically be embodied by computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and includes any information delivery media.
- modulated data signal may describe a signal that has one or more characteristics set or changed in such a manner as to encode information in the signal.
- communication media may include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), infrared, and other wireless media.
- wireless media such as acoustic, radio frequency (RF), infrared, and other wireless media.
- RF radio frequency
- computer readable media may include both storage media and communication media.
- program modules and data files may be stored in system memory 404, including operating system 405.
- programming modules 406 e.g., personal assistant program 112 may perform processes including, for example, one or more of method 200's stages as described above. The aforementioned process is an example, and processing unit 402 may perform other processes.
- Other programming modules that may be used in accordance with
- embodiments of the present invention may include electronic mail and contacts applications, word processing applications, spreadsheet applications, database
- program modules may include routines, programs, components, data structures, and other types of structures that may perform particular tasks or that may implement particular abstract data types.
- embodiments of the invention may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor- based or programmable consumer electronics, minicomputers, mainframe computers, and the like.
- Embodiments of the invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network.
- program modules may be located in both local and remote memory storage devices.
- embodiments of the invention may be practiced in an electrical circuit comprising discrete electronic elements, packaged or integrated electronic chips containing logic gates, a circuit utilizing a microprocessor, or on a single chip containing electronic elements or microprocessors.
- Embodiments of the invention may also be practiced using other technologies capable of performing logical operations such as, for example, AND, OR, and NOT, including but not limited to, mechanical, optical, fluidic, and quantum technologies.
- embodiments of the invention may be practiced within a general purpose computer or in any other circuits or systems.
- Embodiments of the invention may be implemented as a computer process (method), a computing system, or as an article of manufacture, such as a computer program product or computer readable media.
- the computer program product may be a computer storage media readable by a computer system and encoding a computer program of instructions for executing a computer process.
- the computer program product may also be a propagated signal on a carrier readable by a computing system and encoding a computer program of instructions for executing a computer process.
- the present invention may be embodied in hardware and/or in software (including firmware, resident software, micro-code, etc.).
- embodiments of the present invention may take the form of a computer program product on a computer-usable or computer-readable storage medium having computer-usable or computer-readable program code embodied in the medium for use by or in connection with an instruction execution system.
- a computer-usable or computer-readable medium may be any medium that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
- the computer-usable or computer-readable medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. More specific computer-readable medium examples (a non-exhaustive list), the computer-readable medium may include the following: an electrical connection having one or more wires, a portable computer diskette, a random access memory (RAM), a read-only memory
- ROM read-only memory
- EPROM or Flash memory erasable programmable read-only memory
- CD-ROM portable compact disc read-only memory
- the computer-usable or computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
Abstract
Applications Claiming Priority (8)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US13/076,862 US9760566B2 (en) | 2011-03-31 | 2011-03-31 | Augmented conversational understanding agent to identify conversation context between two humans and taking an agent action thereof |
US13/077,431 US10642934B2 (en) | 2011-03-31 | 2011-03-31 | Augmented conversational understanding architecture |
US13/077,368 US9298287B2 (en) | 2011-03-31 | 2011-03-31 | Combined activation for natural user interface systems |
US13/077,303 US9858343B2 (en) | 2011-03-31 | 2011-03-31 | Personalization of queries, conversations, and searches |
US13/077,233 US20120253789A1 (en) | 2011-03-31 | 2011-03-31 | Conversational Dialog Learning and Correction |
US13/077,396 US9842168B2 (en) | 2011-03-31 | 2011-03-31 | Task driven user intents |
US13/077,455 US9244984B2 (en) | 2011-03-31 | 2011-03-31 | Location based conversational understanding |
PCT/US2012/031736 WO2012135791A2 (fr) | 2011-03-31 | 2012-03-30 | Personnalisation de requêtes, de conversations et de recherches |
Publications (2)
Publication Number | Publication Date |
---|---|
EP2691876A2 true EP2691876A2 (fr) | 2014-02-05 |
EP2691876A4 EP2691876A4 (fr) | 2015-06-10 |
Family
ID=46931884
Family Applications (6)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP12765896.1A Withdrawn EP2691877A4 (fr) | 2011-03-31 | 2012-03-27 | Apprentissage et correction d'un dialogue conversationnel |
EP12764494.6A Ceased EP2691870A4 (fr) | 2011-03-31 | 2012-03-27 | Intentions d'utilisateurs orientées sur les tâches |
EP12763913.6A Ceased EP2691885A4 (fr) | 2011-03-31 | 2012-03-27 | Architecture de compréhension conversationnelle augmentée |
EP12763866.6A Ceased EP2691949A4 (fr) | 2011-03-31 | 2012-03-27 | Compréhension conversationnelle basée sur l'emplacement |
EP12765100.8A Ceased EP2691876A4 (fr) | 2011-03-31 | 2012-03-30 | Personnalisation de requêtes, de conversations et de recherches |
EP12764853.3A Ceased EP2691875A4 (fr) | 2011-03-31 | 2012-03-30 | Agent augmenté de compréhension de la conversation |
Family Applications Before (4)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP12765896.1A Withdrawn EP2691877A4 (fr) | 2011-03-31 | 2012-03-27 | Apprentissage et correction d'un dialogue conversationnel |
EP12764494.6A Ceased EP2691870A4 (fr) | 2011-03-31 | 2012-03-27 | Intentions d'utilisateurs orientées sur les tâches |
EP12763913.6A Ceased EP2691885A4 (fr) | 2011-03-31 | 2012-03-27 | Architecture de compréhension conversationnelle augmentée |
EP12763866.6A Ceased EP2691949A4 (fr) | 2011-03-31 | 2012-03-27 | Compréhension conversationnelle basée sur l'emplacement |
Family Applications After (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP12764853.3A Ceased EP2691875A4 (fr) | 2011-03-31 | 2012-03-30 | Agent augmenté de compréhension de la conversation |
Country Status (5)
Country | Link |
---|---|
EP (6) | EP2691877A4 (fr) |
JP (4) | JP2014512046A (fr) |
KR (3) | KR20140014200A (fr) |
CN (8) | CN102737096B (fr) |
WO (7) | WO2012135210A2 (fr) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110019718A (zh) * | 2017-12-15 | 2019-07-16 | 上海智臻智能网络科技股份有限公司 | 修改多轮问答系统的方法、终端设备以及存储介质 |
US11341422B2 (en) | 2017-12-15 | 2022-05-24 | SHANGHAI XIAOl ROBOT TECHNOLOGY CO., LTD. | Multi-round questioning and answering methods, methods for generating a multi-round questioning and answering system, and methods for modifying the system |
Families Citing this family (203)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8677377B2 (en) | 2005-09-08 | 2014-03-18 | Apple Inc. | Method and apparatus for building an intelligent automated assistant |
US9318108B2 (en) | 2010-01-18 | 2016-04-19 | Apple Inc. | Intelligent automated assistant |
US8977255B2 (en) | 2007-04-03 | 2015-03-10 | Apple Inc. | Method and system for operating a multi-function portable electronic device using voice-activation |
US10002189B2 (en) | 2007-12-20 | 2018-06-19 | Apple Inc. | Method and apparatus for searching using an active ontology |
US9330720B2 (en) | 2008-01-03 | 2016-05-03 | Apple Inc. | Methods and apparatus for altering audio output signals |
US8996376B2 (en) | 2008-04-05 | 2015-03-31 | Apple Inc. | Intelligent text-to-speech conversion |
US20100030549A1 (en) | 2008-07-31 | 2010-02-04 | Lee Michael M | Mobile device having human language translation capability with positional feedback |
US8676904B2 (en) | 2008-10-02 | 2014-03-18 | Apple Inc. | Electronic devices with voice command and contextual data processing capabilities |
US10241752B2 (en) | 2011-09-30 | 2019-03-26 | Apple Inc. | Interface for a virtual digital assistant |
US10241644B2 (en) | 2011-06-03 | 2019-03-26 | Apple Inc. | Actionable reminder entries |
US10706373B2 (en) | 2011-06-03 | 2020-07-07 | Apple Inc. | Performing actions associated with task items that represent tasks to perform |
US10276170B2 (en) | 2010-01-18 | 2019-04-30 | Apple Inc. | Intelligent automated assistant |
US8682667B2 (en) | 2010-02-25 | 2014-03-25 | Apple Inc. | User profiling for selecting user specific voice input processing information |
US10032127B2 (en) | 2011-02-18 | 2018-07-24 | Nuance Communications, Inc. | Methods and apparatus for determining a clinician's intent to order an item |
US9262612B2 (en) | 2011-03-21 | 2016-02-16 | Apple Inc. | Device access using voice authentication |
US9842168B2 (en) | 2011-03-31 | 2017-12-12 | Microsoft Technology Licensing, Llc | Task driven user intents |
US10642934B2 (en) | 2011-03-31 | 2020-05-05 | Microsoft Technology Licensing, Llc | Augmented conversational understanding architecture |
US9760566B2 (en) | 2011-03-31 | 2017-09-12 | Microsoft Technology Licensing, Llc | Augmented conversational understanding agent to identify conversation context between two humans and taking an agent action thereof |
US9064006B2 (en) | 2012-08-23 | 2015-06-23 | Microsoft Technology Licensing, Llc | Translating natural language utterances to keyword search queries |
US10057736B2 (en) | 2011-06-03 | 2018-08-21 | Apple Inc. | Active transport based notifications |
US10134385B2 (en) | 2012-03-02 | 2018-11-20 | Apple Inc. | Systems and methods for name pronunciation |
US10417037B2 (en) | 2012-05-15 | 2019-09-17 | Apple Inc. | Systems and methods for integrating third party services with a digital assistant |
US9721563B2 (en) | 2012-06-08 | 2017-08-01 | Apple Inc. | Name recognition system |
WO2014025990A1 (fr) | 2012-08-10 | 2014-02-13 | Nuance Communications, Inc. | Communication d'agent virtuel pour des dispositifs électroniques |
US9547647B2 (en) | 2012-09-19 | 2017-01-17 | Apple Inc. | Voice-based media searching |
CN104969289B (zh) | 2013-02-07 | 2021-05-28 | 苹果公司 | 数字助理的语音触发器 |
EP2946322A1 (fr) * | 2013-03-01 | 2015-11-25 | Nuance Communications, Inc. | Procédés et appareil pour déterminer l'intention d'un clinicien de commander un article |
US10652394B2 (en) | 2013-03-14 | 2020-05-12 | Apple Inc. | System and method for processing voicemail |
US10748529B1 (en) | 2013-03-15 | 2020-08-18 | Apple Inc. | Voice activated device for use with a voice-based digital assistant |
US9436287B2 (en) * | 2013-03-15 | 2016-09-06 | Qualcomm Incorporated | Systems and methods for switching processing modes using gestures |
WO2014197334A2 (fr) | 2013-06-07 | 2014-12-11 | Apple Inc. | Système et procédé destinés à une prononciation de mots spécifiée par l'utilisateur dans la synthèse et la reconnaissance de la parole |
WO2014197335A1 (fr) | 2013-06-08 | 2014-12-11 | Apple Inc. | Interprétation et action sur des commandes qui impliquent un partage d'informations avec des dispositifs distants |
US10176167B2 (en) | 2013-06-09 | 2019-01-08 | Apple Inc. | System and method for inferring user intent from speech inputs |
KR101959188B1 (ko) | 2013-06-09 | 2019-07-02 | 애플 인크. | 디지털 어시스턴트의 둘 이상의 인스턴스들에 걸친 대화 지속성을 가능하게 하기 위한 디바이스, 방법 및 그래픽 사용자 인터페이스 |
US9728184B2 (en) | 2013-06-18 | 2017-08-08 | Microsoft Technology Licensing, Llc | Restructuring deep neural network acoustic models |
US9589565B2 (en) * | 2013-06-21 | 2017-03-07 | Microsoft Technology Licensing, Llc | Environmentally aware dialog policies and response generation |
US9311298B2 (en) | 2013-06-21 | 2016-04-12 | Microsoft Technology Licensing, Llc | Building conversational understanding systems using a toolset |
US10296160B2 (en) | 2013-12-06 | 2019-05-21 | Apple Inc. | Method for extracting salient dialog usage from live data |
CN104714954A (zh) * | 2013-12-13 | 2015-06-17 | 中国电信股份有限公司 | 基于上下文理解的信息搜索方法和系统 |
US20150170053A1 (en) * | 2013-12-13 | 2015-06-18 | Microsoft Corporation | Personalized machine learning models |
US10534623B2 (en) | 2013-12-16 | 2020-01-14 | Nuance Communications, Inc. | Systems and methods for providing a virtual assistant |
US10015770B2 (en) | 2014-03-24 | 2018-07-03 | International Business Machines Corporation | Social proximity networks for mobile phones |
US9529794B2 (en) | 2014-03-27 | 2016-12-27 | Microsoft Technology Licensing, Llc | Flexible schema for language model customization |
US20150278370A1 (en) * | 2014-04-01 | 2015-10-01 | Microsoft Corporation | Task completion for natural language input |
US10111099B2 (en) | 2014-05-12 | 2018-10-23 | Microsoft Technology Licensing, Llc | Distributing content in managed wireless distribution networks |
US9874914B2 (en) | 2014-05-19 | 2018-01-23 | Microsoft Technology Licensing, Llc | Power management contracts for accessory devices |
US9633004B2 (en) | 2014-05-30 | 2017-04-25 | Apple Inc. | Better resolution when referencing to concepts |
US10170123B2 (en) | 2014-05-30 | 2019-01-01 | Apple Inc. | Intelligent assistant for home automation |
US9715875B2 (en) | 2014-05-30 | 2017-07-25 | Apple Inc. | Reducing the need for manual start/end-pointing and trigger phrases |
US9966065B2 (en) | 2014-05-30 | 2018-05-08 | Apple Inc. | Multi-command single utterance input method |
US9430463B2 (en) | 2014-05-30 | 2016-08-30 | Apple Inc. | Exemplar-based natural language processing |
US9355640B2 (en) * | 2014-06-04 | 2016-05-31 | Google Inc. | Invoking action responsive to co-presence determination |
US9717006B2 (en) | 2014-06-23 | 2017-07-25 | Microsoft Technology Licensing, Llc | Device quarantine in a wireless network |
JP6275569B2 (ja) | 2014-06-27 | 2018-02-07 | 株式会社東芝 | 対話装置、方法およびプログラム |
US9338493B2 (en) | 2014-06-30 | 2016-05-10 | Apple Inc. | Intelligent automated assistant for TV user interactions |
US9916328B1 (en) | 2014-07-11 | 2018-03-13 | Google Llc | Providing user assistance from interaction understanding |
US10146409B2 (en) * | 2014-08-29 | 2018-12-04 | Microsoft Technology Licensing, Llc | Computerized dynamic splitting of interaction across multiple content |
US9818400B2 (en) | 2014-09-11 | 2017-11-14 | Apple Inc. | Method and apparatus for discovering trending terms in speech requests |
US10074360B2 (en) | 2014-09-30 | 2018-09-11 | Apple Inc. | Providing an indication of the suitability of speech recognition |
US9668121B2 (en) | 2014-09-30 | 2017-05-30 | Apple Inc. | Social reminders |
US10127911B2 (en) | 2014-09-30 | 2018-11-13 | Apple Inc. | Speaker identification and unsupervised speaker adaptation techniques |
KR102188268B1 (ko) * | 2014-10-08 | 2020-12-08 | 엘지전자 주식회사 | 이동단말기 및 그 제어방법 |
EP3210096B1 (fr) * | 2014-10-21 | 2019-05-15 | Robert Bosch GmbH | Procédé et système pour l'automatisation de la sélection et de la composition de réponses dans des systèmes de dialogue |
KR102329333B1 (ko) * | 2014-11-12 | 2021-11-23 | 삼성전자주식회사 | 질의를 처리하는 장치 및 방법 |
US9836452B2 (en) * | 2014-12-30 | 2017-12-05 | Microsoft Technology Licensing, Llc | Discriminating ambiguous expressions to enhance user experience |
US10713005B2 (en) | 2015-01-05 | 2020-07-14 | Google Llc | Multimodal state circulation |
US10572810B2 (en) | 2015-01-07 | 2020-02-25 | Microsoft Technology Licensing, Llc | Managing user interaction for input understanding determinations |
WO2016129767A1 (fr) * | 2015-02-13 | 2016-08-18 | 주식회사 팔락성 | Procédé de liaison de sites en ligne |
US10152299B2 (en) | 2015-03-06 | 2018-12-11 | Apple Inc. | Reducing response latency of intelligent automated assistants |
US10567477B2 (en) | 2015-03-08 | 2020-02-18 | Apple Inc. | Virtual assistant continuity |
US9721566B2 (en) | 2015-03-08 | 2017-08-01 | Apple Inc. | Competing devices responding to voice triggers |
US9886953B2 (en) | 2015-03-08 | 2018-02-06 | Apple Inc. | Virtual assistant activation |
US10460227B2 (en) | 2015-05-15 | 2019-10-29 | Apple Inc. | Virtual assistant in a communication session |
US10083688B2 (en) | 2015-05-27 | 2018-09-25 | Apple Inc. | Device voice control for selecting a displayed affordance |
US10200824B2 (en) | 2015-05-27 | 2019-02-05 | Apple Inc. | Systems and methods for proactively identifying and surfacing relevant content on a touch-sensitive device |
US9578173B2 (en) | 2015-06-05 | 2017-02-21 | Apple Inc. | Virtual assistant aided communication with 3rd party service in a communication session |
US11025565B2 (en) | 2015-06-07 | 2021-06-01 | Apple Inc. | Personalized prediction of responses for instant messaging |
US9792281B2 (en) * | 2015-06-15 | 2017-10-17 | Microsoft Technology Licensing, Llc | Contextual language generation by leveraging language understanding |
US20160378747A1 (en) | 2015-06-29 | 2016-12-29 | Apple Inc. | Virtual assistant for media playback |
US10249297B2 (en) | 2015-07-13 | 2019-04-02 | Microsoft Technology Licensing, Llc | Propagating conversational alternatives using delayed hypothesis binding |
US10740384B2 (en) | 2015-09-08 | 2020-08-11 | Apple Inc. | Intelligent automated assistant for media search and playback |
US10331312B2 (en) | 2015-09-08 | 2019-06-25 | Apple Inc. | Intelligent automated assistant in a media environment |
US10747498B2 (en) | 2015-09-08 | 2020-08-18 | Apple Inc. | Zero latency digital assistant |
US10671428B2 (en) | 2015-09-08 | 2020-06-02 | Apple Inc. | Distributed personal assistant |
KR20170033722A (ko) * | 2015-09-17 | 2017-03-27 | 삼성전자주식회사 | 사용자의 발화 처리 장치 및 방법과, 음성 대화 관리 장치 |
US10262654B2 (en) * | 2015-09-24 | 2019-04-16 | Microsoft Technology Licensing, Llc | Detecting actionable items in a conversation among participants |
US10970646B2 (en) | 2015-10-01 | 2021-04-06 | Google Llc | Action suggestions for user-selected content |
US10691473B2 (en) | 2015-11-06 | 2020-06-23 | Apple Inc. | Intelligent automated assistant in a messaging environment |
US10956666B2 (en) | 2015-11-09 | 2021-03-23 | Apple Inc. | Unconventional virtual assistant interactions |
KR102393928B1 (ko) | 2015-11-10 | 2022-05-04 | 삼성전자주식회사 | 응답 메시지를 추천하는 사용자 단말 장치 및 그 방법 |
WO2017090954A1 (fr) * | 2015-11-24 | 2017-06-01 | Samsung Electronics Co., Ltd. | Dispositif électronique et procédé de fonctionnement associé |
US10049668B2 (en) | 2015-12-02 | 2018-08-14 | Apple Inc. | Applying neural network language models to weighted finite state transducers for automatic speech recognition |
KR102502569B1 (ko) | 2015-12-02 | 2023-02-23 | 삼성전자주식회사 | 시스템 리소스 관리를 위한 방법 및 장치 |
US10223066B2 (en) | 2015-12-23 | 2019-03-05 | Apple Inc. | Proactive assistance based on dialog communication between devices |
US9905248B2 (en) | 2016-02-29 | 2018-02-27 | International Business Machines Corporation | Inferring user intentions based on user conversation data and spatio-temporal data |
US9978396B2 (en) | 2016-03-16 | 2018-05-22 | International Business Machines Corporation | Graphical display of phone conversations |
US10587708B2 (en) * | 2016-03-28 | 2020-03-10 | Microsoft Technology Licensing, Llc | Multi-modal conversational intercom |
US11487512B2 (en) | 2016-03-29 | 2022-11-01 | Microsoft Technology Licensing, Llc | Generating a services application |
US10158593B2 (en) * | 2016-04-08 | 2018-12-18 | Microsoft Technology Licensing, Llc | Proactive intelligent personal assistant |
US10945129B2 (en) * | 2016-04-29 | 2021-03-09 | Microsoft Technology Licensing, Llc | Facilitating interaction among digital personal assistants |
US10409876B2 (en) * | 2016-05-26 | 2019-09-10 | Microsoft Technology Licensing, Llc. | Intelligent capture, storage, and retrieval of information for task completion |
WO2017210613A1 (fr) * | 2016-06-03 | 2017-12-07 | Maluuba Inc. | Production de langage naturel dans un système de dialogue parlé |
US11227589B2 (en) | 2016-06-06 | 2022-01-18 | Apple Inc. | Intelligent list reading |
US10249300B2 (en) | 2016-06-06 | 2019-04-02 | Apple Inc. | Intelligent list reading |
US10282218B2 (en) * | 2016-06-07 | 2019-05-07 | Google Llc | Nondeterministic task initiation by a personal assistant module |
US10049663B2 (en) | 2016-06-08 | 2018-08-14 | Apple, Inc. | Intelligent automated assistant for media exploration |
DK179309B1 (en) | 2016-06-09 | 2018-04-23 | Apple Inc | Intelligent automated assistant in a home environment |
US10586535B2 (en) | 2016-06-10 | 2020-03-10 | Apple Inc. | Intelligent digital assistant in a multi-tasking environment |
US10067938B2 (en) | 2016-06-10 | 2018-09-04 | Apple Inc. | Multilingual word prediction |
DK179343B1 (en) | 2016-06-11 | 2018-05-14 | Apple Inc | Intelligent task discovery |
DK179415B1 (en) | 2016-06-11 | 2018-06-14 | Apple Inc | Intelligent device arbitration and control |
DK201670540A1 (en) | 2016-06-11 | 2018-01-08 | Apple Inc | Application integration with a digital assistant |
US10216269B2 (en) * | 2016-06-21 | 2019-02-26 | GM Global Technology Operations LLC | Apparatus and method for determining intent of user based on gaze information |
WO2018039272A1 (fr) * | 2016-08-23 | 2018-03-01 | Illumina, Inc. | Systèmes de distance sémantique et procédés de détermination de données ontologiques associées |
US10474753B2 (en) | 2016-09-07 | 2019-11-12 | Apple Inc. | Language identification using recurrent neural networks |
US10446137B2 (en) | 2016-09-07 | 2019-10-15 | Microsoft Technology Licensing, Llc | Ambiguity resolving conversational understanding system |
US10503767B2 (en) * | 2016-09-13 | 2019-12-10 | Microsoft Technology Licensing, Llc | Computerized natural language query intent dispatching |
US10043516B2 (en) | 2016-09-23 | 2018-08-07 | Apple Inc. | Intelligent automated assistant |
US9940390B1 (en) * | 2016-09-27 | 2018-04-10 | Microsoft Technology Licensing, Llc | Control system using scoped search and conversational interface |
CN107885744B (zh) | 2016-09-29 | 2023-01-03 | 微软技术许可有限责任公司 | 对话式的数据分析 |
US10535005B1 (en) | 2016-10-26 | 2020-01-14 | Google Llc | Providing contextual actions for mobile onscreen content |
JP6697373B2 (ja) | 2016-12-06 | 2020-05-20 | カシオ計算機株式会社 | 文生成装置、文生成方法及びプログラム |
US10593346B2 (en) | 2016-12-22 | 2020-03-17 | Apple Inc. | Rank-reduced token representation for automatic speech recognition |
US11204787B2 (en) | 2017-01-09 | 2021-12-21 | Apple Inc. | Application integration with a digital assistant |
EP3552114A4 (fr) * | 2017-02-08 | 2020-05-20 | Semantic Machines, Inc. | Générateur de contenu en langage naturel |
US10643601B2 (en) * | 2017-02-09 | 2020-05-05 | Semantic Machines, Inc. | Detection mechanism for automated dialog systems |
WO2018156978A1 (fr) | 2017-02-23 | 2018-08-30 | Semantic Machines, Inc. | Système de dialogue évolutif |
CN110301004B (zh) * | 2017-02-23 | 2023-08-08 | 微软技术许可有限责任公司 | 可扩展对话系统 |
US10798027B2 (en) * | 2017-03-05 | 2020-10-06 | Microsoft Technology Licensing, Llc | Personalized communications using semantic memory |
US10237209B2 (en) * | 2017-05-08 | 2019-03-19 | Google Llc | Initializing a conversation with an automated agent via selectable graphical element |
US10417266B2 (en) | 2017-05-09 | 2019-09-17 | Apple Inc. | Context-aware ranking of intelligent response suggestions |
DK201770383A1 (en) | 2017-05-09 | 2018-12-14 | Apple Inc. | USER INTERFACE FOR CORRECTING RECOGNITION ERRORS |
DK180048B1 (en) | 2017-05-11 | 2020-02-04 | Apple Inc. | MAINTAINING THE DATA PROTECTION OF PERSONAL INFORMATION |
US10395654B2 (en) | 2017-05-11 | 2019-08-27 | Apple Inc. | Text normalization based on a data-driven learning network |
DK201770439A1 (en) | 2017-05-11 | 2018-12-13 | Apple Inc. | Offline personal assistant |
US10726832B2 (en) | 2017-05-11 | 2020-07-28 | Apple Inc. | Maintaining privacy of personal information |
DK179496B1 (en) | 2017-05-12 | 2019-01-15 | Apple Inc. | USER-SPECIFIC Acoustic Models |
DK179745B1 (en) | 2017-05-12 | 2019-05-01 | Apple Inc. | SYNCHRONIZATION AND TASK DELEGATION OF A DIGITAL ASSISTANT |
DK201770427A1 (en) | 2017-05-12 | 2018-12-20 | Apple Inc. | LOW-LATENCY INTELLIGENT AUTOMATED ASSISTANT |
US11301477B2 (en) | 2017-05-12 | 2022-04-12 | Apple Inc. | Feedback analysis of a digital assistant |
DK201770432A1 (en) | 2017-05-15 | 2018-12-21 | Apple Inc. | Hierarchical belief states for digital assistants |
DK201770431A1 (en) | 2017-05-15 | 2018-12-20 | Apple Inc. | Optimizing dialogue policy decisions for digital assistants using implicit feedback |
US10311144B2 (en) | 2017-05-16 | 2019-06-04 | Apple Inc. | Emoji word sense disambiguation |
DK179560B1 (en) | 2017-05-16 | 2019-02-18 | Apple Inc. | FAR-FIELD EXTENSION FOR DIGITAL ASSISTANT SERVICES |
US10403278B2 (en) | 2017-05-16 | 2019-09-03 | Apple Inc. | Methods and systems for phonetic matching in digital assistant services |
US20180336892A1 (en) | 2017-05-16 | 2018-11-22 | Apple Inc. | Detecting a trigger of a digital assistant |
US10303715B2 (en) | 2017-05-16 | 2019-05-28 | Apple Inc. | Intelligent automated assistant for media exploration |
US10664533B2 (en) * | 2017-05-24 | 2020-05-26 | Lenovo (Singapore) Pte. Ltd. | Systems and methods to determine response cue for digital assistant based on context |
US10679192B2 (en) | 2017-05-25 | 2020-06-09 | Microsoft Technology Licensing, Llc | Assigning tasks and monitoring task performance based on context extracted from a shared contextual graph |
US10657328B2 (en) | 2017-06-02 | 2020-05-19 | Apple Inc. | Multi-task recurrent neural network architecture for efficient morphology handling in neural language modeling |
US10742435B2 (en) * | 2017-06-29 | 2020-08-11 | Google Llc | Proactive provision of new content to group chat participants |
US11132499B2 (en) | 2017-08-28 | 2021-09-28 | Microsoft Technology Licensing, Llc | Robust expandable dialogue system |
US10445429B2 (en) | 2017-09-21 | 2019-10-15 | Apple Inc. | Natural language understanding using vocabularies with compressed serialized tries |
US10755051B2 (en) | 2017-09-29 | 2020-08-25 | Apple Inc. | Rule-based natural language processing |
US10546023B2 (en) | 2017-10-03 | 2020-01-28 | Google Llc | Providing command bundle suggestions for an automated assistant |
US10636424B2 (en) | 2017-11-30 | 2020-04-28 | Apple Inc. | Multi-turn canned dialog |
US10733982B2 (en) | 2018-01-08 | 2020-08-04 | Apple Inc. | Multi-directional dialog |
US10839160B2 (en) * | 2018-01-19 | 2020-11-17 | International Business Machines Corporation | Ontology-based automatic bootstrapping of state-based dialog systems |
US10733375B2 (en) | 2018-01-31 | 2020-08-04 | Apple Inc. | Knowledge-based framework for improving natural language understanding |
US10789959B2 (en) | 2018-03-02 | 2020-09-29 | Apple Inc. | Training speaker recognition models for digital assistants |
US10592604B2 (en) | 2018-03-12 | 2020-03-17 | Apple Inc. | Inverse text normalization for automatic speech recognition |
KR102635811B1 (ko) * | 2018-03-19 | 2024-02-13 | 삼성전자 주식회사 | 사운드 데이터를 처리하는 시스템 및 시스템의 제어 방법 |
US10818288B2 (en) | 2018-03-26 | 2020-10-27 | Apple Inc. | Natural assistant interaction |
US10909331B2 (en) | 2018-03-30 | 2021-02-02 | Apple Inc. | Implicit identification of translation payload with neural machine translation |
US10685075B2 (en) * | 2018-04-11 | 2020-06-16 | Motorola Solutions, Inc. | System and method for tailoring an electronic digital assistant query as a function of captured multi-party voice dialog and an electronically stored multi-party voice-interaction template |
US10928918B2 (en) | 2018-05-07 | 2021-02-23 | Apple Inc. | Raise to speak |
US11145294B2 (en) | 2018-05-07 | 2021-10-12 | Apple Inc. | Intelligent automated assistant for delivering content from user experiences |
US10984780B2 (en) | 2018-05-21 | 2021-04-20 | Apple Inc. | Global semantic word embeddings using bi-directional recurrent neural networks |
DK179822B1 (da) | 2018-06-01 | 2019-07-12 | Apple Inc. | Voice interaction at a primary device to access call functionality of a companion device |
US11386266B2 (en) | 2018-06-01 | 2022-07-12 | Apple Inc. | Text correction |
DK180639B1 (en) | 2018-06-01 | 2021-11-04 | Apple Inc | DISABILITY OF ATTENTION-ATTENTIVE VIRTUAL ASSISTANT |
US10892996B2 (en) | 2018-06-01 | 2021-01-12 | Apple Inc. | Variable latency device coordination |
DK201870355A1 (en) | 2018-06-01 | 2019-12-16 | Apple Inc. | VIRTUAL ASSISTANT OPERATION IN MULTI-DEVICE ENVIRONMENTS |
US10496705B1 (en) | 2018-06-03 | 2019-12-03 | Apple Inc. | Accelerated task performance |
JP7018589B2 (ja) | 2018-08-29 | 2022-02-14 | パナソニックIpマネジメント株式会社 | 電力変換システム及び蓄電システム |
US11010561B2 (en) | 2018-09-27 | 2021-05-18 | Apple Inc. | Sentiment prediction from textual data |
US10839159B2 (en) | 2018-09-28 | 2020-11-17 | Apple Inc. | Named entity normalization in a spoken dialog system |
US11462215B2 (en) | 2018-09-28 | 2022-10-04 | Apple Inc. | Multi-modal inputs for voice commands |
US11170166B2 (en) | 2018-09-28 | 2021-11-09 | Apple Inc. | Neural typographical error modeling via generative adversarial networks |
US11475898B2 (en) | 2018-10-26 | 2022-10-18 | Apple Inc. | Low-latency multi-speaker speech recognition |
US11638059B2 (en) | 2019-01-04 | 2023-04-25 | Apple Inc. | Content playback on multiple devices |
CN111428721A (zh) * | 2019-01-10 | 2020-07-17 | 北京字节跳动网络技术有限公司 | 词语释义的确定方法、装置、设备及存储介质 |
US11348573B2 (en) | 2019-03-18 | 2022-05-31 | Apple Inc. | Multimodality in digital assistant systems |
US11423908B2 (en) | 2019-05-06 | 2022-08-23 | Apple Inc. | Interpreting spoken requests |
US11307752B2 (en) | 2019-05-06 | 2022-04-19 | Apple Inc. | User configurable task triggers |
DK201970509A1 (en) | 2019-05-06 | 2021-01-15 | Apple Inc | Spoken notifications |
US11475884B2 (en) | 2019-05-06 | 2022-10-18 | Apple Inc. | Reducing digital assistant latency when a language is incorrectly determined |
US11140099B2 (en) | 2019-05-21 | 2021-10-05 | Apple Inc. | Providing message response suggestions |
US11289073B2 (en) | 2019-05-31 | 2022-03-29 | Apple Inc. | Device text to speech |
US11496600B2 (en) | 2019-05-31 | 2022-11-08 | Apple Inc. | Remote execution of machine-learned models |
DK201970510A1 (en) | 2019-05-31 | 2021-02-11 | Apple Inc | Voice identification in digital assistant systems |
DK180129B1 (en) | 2019-05-31 | 2020-06-02 | Apple Inc. | USER ACTIVITY SHORTCUT SUGGESTIONS |
US11360641B2 (en) | 2019-06-01 | 2022-06-14 | Apple Inc. | Increasing the relevance of new available information |
US11227599B2 (en) | 2019-06-01 | 2022-01-18 | Apple Inc. | Methods and user interfaces for voice-based control of electronic devices |
US11488406B2 (en) | 2019-09-25 | 2022-11-01 | Apple Inc. | Text detection using global geometry estimators |
US11043220B1 (en) | 2020-05-11 | 2021-06-22 | Apple Inc. | Digital assistant hardware abstraction |
US11061543B1 (en) | 2020-05-11 | 2021-07-13 | Apple Inc. | Providing relevant data items based on context |
US11755276B2 (en) | 2020-05-12 | 2023-09-12 | Apple Inc. | Reducing description length based on confidence |
US11490204B2 (en) | 2020-07-20 | 2022-11-01 | Apple Inc. | Multi-device audio adjustment coordination |
US11438683B2 (en) | 2020-07-21 | 2022-09-06 | Apple Inc. | User identification using headphones |
US11783827B2 (en) | 2020-11-06 | 2023-10-10 | Apple Inc. | Determining suggested subsequent user actions during digital assistant interaction |
EP4174848A1 (fr) * | 2021-10-29 | 2023-05-03 | Televic Rail NV | Procédé et système améliorés de la parole en texte |
CN116644810B (zh) * | 2023-05-06 | 2024-04-05 | 国网冀北电力有限公司信息通信分公司 | 一种基于知识图谱实现的电网故障风险处置方法及装置 |
Family Cites Families (72)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5265014A (en) * | 1990-04-10 | 1993-11-23 | Hewlett-Packard Company | Multi-modal user interface |
US5748974A (en) * | 1994-12-13 | 1998-05-05 | International Business Machines Corporation | Multimodal natural language interface for cross-application tasks |
US5970446A (en) * | 1997-11-25 | 1999-10-19 | At&T Corp | Selective noise/channel/coding models and recognizers for automatic speech recognition |
CN1313972A (zh) * | 1998-08-24 | 2001-09-19 | Bcl计算机有限公司 | 自适应的自然语言接口 |
US6499013B1 (en) * | 1998-09-09 | 2002-12-24 | One Voice Technologies, Inc. | Interactive user interface using speech recognition and natural language processing |
US6332120B1 (en) * | 1999-04-20 | 2001-12-18 | Solana Technology Development Corporation | Broadcast speech recognition system for keyword monitoring |
JP3530109B2 (ja) * | 1999-05-31 | 2004-05-24 | 日本電信電話株式会社 | 大規模情報データベースに対する音声対話型情報検索方法、装置および記録媒体 |
EP1236096A1 (fr) * | 1999-06-01 | 2002-09-04 | Geoffrey M. Jacquez | Systeme d'aide pour application informatique |
US6598039B1 (en) * | 1999-06-08 | 2003-07-22 | Albert-Inc. S.A. | Natural language interface for searching database |
JP3765202B2 (ja) * | 1999-07-09 | 2006-04-12 | 日産自動車株式会社 | 対話型情報検索装置、コンピュータを用いた対話型情報検索方法及び対話型情報検索処理を行うプログラムを記録したコンピュータ読取り可能な媒体 |
JP2001125896A (ja) * | 1999-10-26 | 2001-05-11 | Victor Co Of Japan Ltd | 自然言語対話システム |
US7050977B1 (en) * | 1999-11-12 | 2006-05-23 | Phoenix Solutions, Inc. | Speech-enabled server for internet website and method |
JP2002024285A (ja) * | 2000-06-30 | 2002-01-25 | Sanyo Electric Co Ltd | ユーザ支援方法およびユーザ支援装置 |
JP2002082748A (ja) * | 2000-09-06 | 2002-03-22 | Sanyo Electric Co Ltd | ユーザ支援装置 |
US7197120B2 (en) * | 2000-12-22 | 2007-03-27 | Openwave Systems Inc. | Method and system for facilitating mediated communication |
GB2372864B (en) * | 2001-02-28 | 2005-09-07 | Vox Generation Ltd | Spoken language interface |
JP2003115951A (ja) * | 2001-10-09 | 2003-04-18 | Casio Comput Co Ltd | 話題情報提供システムおよび話題情報提供方法 |
US7224981B2 (en) * | 2002-06-20 | 2007-05-29 | Intel Corporation | Speech recognition of mobile devices |
US7693720B2 (en) * | 2002-07-15 | 2010-04-06 | Voicebox Technologies, Inc. | Mobile systems and methods for responding to natural language speech utterance |
EP1411443A1 (fr) * | 2002-10-18 | 2004-04-21 | Hewlett Packard Company, a Delaware Corporation | Filtrage contextuel |
JP2004212641A (ja) * | 2002-12-27 | 2004-07-29 | Toshiba Corp | 音声入力システム及び音声入力システムを備えた端末装置 |
JP2004328181A (ja) * | 2003-04-23 | 2004-11-18 | Sharp Corp | 電話機及び電話網システム |
JP4441782B2 (ja) * | 2003-05-14 | 2010-03-31 | 日本電信電話株式会社 | 情報提示方法及び情報提示装置 |
JP2005043461A (ja) * | 2003-07-23 | 2005-02-17 | Canon Inc | 音声認識方法及び音声認識装置 |
KR20050032649A (ko) * | 2003-10-02 | 2005-04-08 | (주)이즈메이커 | 인공생명을 학습시키는 방법 및 시스템 |
US7747601B2 (en) * | 2006-08-14 | 2010-06-29 | Inquira, Inc. | Method and apparatus for identifying and classifying query intent |
US7720674B2 (en) * | 2004-06-29 | 2010-05-18 | Sap Ag | Systems and methods for processing natural language queries |
JP4434972B2 (ja) * | 2005-01-21 | 2010-03-17 | 日本電気株式会社 | 情報提供システム、情報提供方法及びそのプログラム |
ATE510259T1 (de) * | 2005-01-31 | 2011-06-15 | Ontoprise Gmbh | Abbilden von web-diensten auf ontologien |
GB0502259D0 (en) * | 2005-02-03 | 2005-03-09 | British Telecomm | Document searching tool and method |
CN101120341A (zh) * | 2005-02-06 | 2008-02-06 | 凌圭特股份有限公司 | 以自然语言进行移动式信息访问的方法和设备 |
US20060206333A1 (en) * | 2005-03-08 | 2006-09-14 | Microsoft Corporation | Speaker-dependent dialog adaptation |
US7409344B2 (en) * | 2005-03-08 | 2008-08-05 | Sap Aktiengesellschaft | XML based architecture for controlling user interfaces with contextual voice commands |
WO2006108061A2 (fr) * | 2005-04-05 | 2006-10-12 | The Board Of Trustees Of Leland Stanford Junior University | Procedes, logiciels et systemes de coordination de base de connaissances |
US7991607B2 (en) * | 2005-06-27 | 2011-08-02 | Microsoft Corporation | Translation and capture architecture for output of conversational utterances |
US7640160B2 (en) * | 2005-08-05 | 2009-12-29 | Voicebox Technologies, Inc. | Systems and methods for responding to natural language speech utterance |
US7620549B2 (en) | 2005-08-10 | 2009-11-17 | Voicebox Technologies, Inc. | System and method of supporting adaptive misrecognition in conversational speech |
US7822699B2 (en) * | 2005-11-30 | 2010-10-26 | Microsoft Corporation | Adaptive semantic reasoning engine |
US7627466B2 (en) * | 2005-11-09 | 2009-12-01 | Microsoft Corporation | Natural language interface for driving adaptive scenarios |
US20070136222A1 (en) * | 2005-12-09 | 2007-06-14 | Microsoft Corporation | Question and answer architecture for reasoning and clarifying intentions, goals, and needs from contextual clues and content |
US20070143410A1 (en) * | 2005-12-16 | 2007-06-21 | International Business Machines Corporation | System and method for defining and translating chat abbreviations |
CN100373313C (zh) * | 2006-01-12 | 2008-03-05 | 广东威创视讯科技股份有限公司 | 一种用于交互式输入设备的智能识别编码方法 |
US8209407B2 (en) * | 2006-02-10 | 2012-06-26 | The United States Of America, As Represented By The Secretary Of The Navy | System and method for web service discovery and access |
US7548909B2 (en) * | 2006-06-13 | 2009-06-16 | Microsoft Corporation | Search engine dash-board |
US20080005068A1 (en) * | 2006-06-28 | 2008-01-03 | Microsoft Corporation | Context-based search, retrieval, and awareness |
CN1963752A (zh) * | 2006-11-28 | 2007-05-16 | 李博航 | 基于自然语言的电子设备人机交互操作界面技术 |
WO2008067676A1 (fr) * | 2006-12-08 | 2008-06-12 | Medhat Moussa | Architecture, système et procédé pour la mise en œuvre d'un réseau neural artificiel |
US20080172359A1 (en) * | 2007-01-11 | 2008-07-17 | Motorola, Inc. | Method and apparatus for providing contextual support to a monitored communication |
US20080172659A1 (en) | 2007-01-17 | 2008-07-17 | Microsoft Corporation | Harmonizing a test file and test configuration in a revision control system |
US20080201434A1 (en) * | 2007-02-16 | 2008-08-21 | Microsoft Corporation | Context-Sensitive Searches and Functionality for Instant Messaging Applications |
US20090076917A1 (en) * | 2007-08-22 | 2009-03-19 | Victor Roditis Jablokov | Facilitating presentation of ads relating to words of a message |
US7720856B2 (en) * | 2007-04-09 | 2010-05-18 | Sap Ag | Cross-language searching |
US8762143B2 (en) * | 2007-05-29 | 2014-06-24 | At&T Intellectual Property Ii, L.P. | Method and apparatus for identifying acoustic background environments based on time and speed to enhance automatic speech recognition |
US7788276B2 (en) * | 2007-08-22 | 2010-08-31 | Yahoo! Inc. | Predictive stemming for web search with statistical machine translation models |
MX2010002350A (es) * | 2007-08-31 | 2010-07-30 | Microsoft Corp | Identificacion de relaciones semanticas dentro de lenguaje reportado. |
US8165886B1 (en) * | 2007-10-04 | 2012-04-24 | Great Northern Research LLC | Speech interface system and method for control and interaction with applications on a computing system |
US8504621B2 (en) * | 2007-10-26 | 2013-08-06 | Microsoft Corporation | Facilitating a decision-making process |
JP2009116733A (ja) * | 2007-11-08 | 2009-05-28 | Nec Corp | アプリケーション検索システム、アプリケーション検索方法、モニタ端末、検索サーバおよびプログラム |
JP5158635B2 (ja) * | 2008-02-28 | 2013-03-06 | インターナショナル・ビジネス・マシーンズ・コーポレーション | パーソナル・サービス支援のための方法、システム、および装置 |
US20090234655A1 (en) * | 2008-03-13 | 2009-09-17 | Jason Kwon | Mobile electronic device with active speech recognition |
WO2009129315A1 (fr) * | 2008-04-15 | 2009-10-22 | Mobile Technologies, Llc | Système et procédés pour maintenir une traduction orale-orale dans le domaine |
CN101499277B (zh) * | 2008-07-25 | 2011-05-04 | 中国科学院计算技术研究所 | 一种服务智能导航方法和系统 |
US8874443B2 (en) * | 2008-08-27 | 2014-10-28 | Robert Bosch Gmbh | System and method for generating natural language phrases from user utterances in dialog systems |
JP2010128665A (ja) * | 2008-11-26 | 2010-06-10 | Kyocera Corp | 情報端末及び会話補助プログラム |
JP2010145262A (ja) * | 2008-12-19 | 2010-07-01 | Pioneer Electronic Corp | ナビゲーション装置 |
US8326637B2 (en) * | 2009-02-20 | 2012-12-04 | Voicebox Technologies, Inc. | System and method for processing multi-modal device interactions in a natural language voice services environment |
JP2010230918A (ja) * | 2009-03-26 | 2010-10-14 | Fujitsu Ten Ltd | 検索装置 |
US8700665B2 (en) * | 2009-04-27 | 2014-04-15 | Avaya Inc. | Intelligent conference call information agents |
US20100281435A1 (en) * | 2009-04-30 | 2010-11-04 | At&T Intellectual Property I, L.P. | System and method for multimodal interaction using robust gesture processing |
KR101622111B1 (ko) * | 2009-12-11 | 2016-05-18 | 삼성전자 주식회사 | 대화 시스템 및 그의 대화 방법 |
KR101007336B1 (ko) * | 2010-06-25 | 2011-01-13 | 한국과학기술정보연구원 | 온톨로지 기반 개인화 서비스 시스템 및 방법 |
US20120253789A1 (en) | 2011-03-31 | 2012-10-04 | Microsoft Corporation | Conversational Dialog Learning and Correction |
-
2012
- 2012-03-27 WO PCT/US2012/030730 patent/WO2012135210A2/fr unknown
- 2012-03-27 JP JP2014502721A patent/JP2014512046A/ja active Pending
- 2012-03-27 KR KR20137025578A patent/KR20140014200A/ko not_active Application Discontinuation
- 2012-03-27 WO PCT/US2012/030740 patent/WO2012135218A2/fr active Application Filing
- 2012-03-27 WO PCT/US2012/030751 patent/WO2012135226A1/fr unknown
- 2012-03-27 EP EP12765896.1A patent/EP2691877A4/fr not_active Withdrawn
- 2012-03-27 WO PCT/US2012/030757 patent/WO2012135229A2/fr active Application Filing
- 2012-03-27 JP JP2014502718A patent/JP6105552B2/ja active Active
- 2012-03-27 KR KR1020137025540A patent/KR101922744B1/ko active IP Right Grant
- 2012-03-27 EP EP12764494.6A patent/EP2691870A4/fr not_active Ceased
- 2012-03-27 WO PCT/US2012/030636 patent/WO2012135157A2/fr unknown
- 2012-03-27 EP EP12763913.6A patent/EP2691885A4/fr not_active Ceased
- 2012-03-27 EP EP12763866.6A patent/EP2691949A4/fr not_active Ceased
- 2012-03-27 KR KR1020137025586A patent/KR101963915B1/ko active IP Right Grant
- 2012-03-27 JP JP2014502723A patent/JP6087899B2/ja not_active Expired - Fee Related
- 2012-03-29 CN CN201210087420.9A patent/CN102737096B/zh active Active
- 2012-03-29 CN CN201610801496.1A patent/CN106383866B/zh active Active
- 2012-03-30 EP EP12765100.8A patent/EP2691876A4/fr not_active Ceased
- 2012-03-30 CN CN201210090349.XA patent/CN102737099B/zh active Active
- 2012-03-30 WO PCT/US2012/031736 patent/WO2012135791A2/fr unknown
- 2012-03-30 CN CN201210091176.3A patent/CN102737101B/zh active Active
- 2012-03-30 CN CN201210090634.1A patent/CN102750311B/zh active Active
- 2012-03-30 EP EP12764853.3A patent/EP2691875A4/fr not_active Ceased
- 2012-03-30 WO PCT/US2012/031722 patent/WO2012135783A2/fr unknown
- 2012-03-31 CN CN201210101485.4A patent/CN102750271B/zh not_active Expired - Fee Related
- 2012-03-31 CN CN201210092263.0A patent/CN102750270B/zh active Active
- 2012-03-31 CN CN201210093414.4A patent/CN102737104B/zh active Active
-
2017
- 2017-03-01 JP JP2017038097A patent/JP6305588B2/ja active Active
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110019718A (zh) * | 2017-12-15 | 2019-07-16 | 上海智臻智能网络科技股份有限公司 | 修改多轮问答系统的方法、终端设备以及存储介质 |
CN110019718B (zh) * | 2017-12-15 | 2021-04-09 | 上海智臻智能网络科技股份有限公司 | 修改多轮问答系统的方法、终端设备以及存储介质 |
US11341422B2 (en) | 2017-12-15 | 2022-05-24 | SHANGHAI XIAOl ROBOT TECHNOLOGY CO., LTD. | Multi-round questioning and answering methods, methods for generating a multi-round questioning and answering system, and methods for modifying the system |
Also Published As
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US9858343B2 (en) | Personalization of queries, conversations, and searches | |
WO2012135791A2 (fr) | Personnalisation de requêtes, de conversations et de recherches | |
US10296587B2 (en) | Augmented conversational understanding agent to identify conversation context between two humans and taking an agent action thereof | |
US10642934B2 (en) | Augmented conversational understanding architecture | |
US10585957B2 (en) | Task driven user intents | |
JP6812473B2 (ja) | メッセージ中のタスクの識別 | |
US10878009B2 (en) | Translating natural language utterances to keyword search queries | |
US10546067B2 (en) | Platform for creating customizable dialog system engines | |
KR102357685B1 (ko) | 병렬 처리용 하이브리드 클라이언트/서버 아키텍처 | |
US20120253789A1 (en) | Conversational Dialog Learning and Correction | |
JP2021524079A (ja) | 自然言語分類のための訓練データの拡張 | |
US20170075985A1 (en) | Query transformation for natural language queries |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PUAI | Public reference made under article 153(3) epc to a published international application that has entered the european phase |
Free format text: ORIGINAL CODE: 0009012 |
|
17P | Request for examination filed |
Effective date: 20130827 |
|
AK | Designated contracting states |
Kind code of ref document: A2 Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR |
|
DAX | Request for extension of the european patent (deleted) | ||
RAP1 | Party data changed (applicant data changed or rights of an application transferred) |
Owner name: MICROSOFT TECHNOLOGY LICENSING, LLC |
|
A4 | Supplementary search report drawn up and despatched |
Effective date: 20150511 |
|
RIC1 | Information provided on ipc code assigned before grant |
Ipc: G06F 17/30 20060101AFI20150504BHEP |
|
17Q | First examination report despatched |
Effective date: 20180718 |
|
REG | Reference to a national code |
Ref country code: DE Ref legal event code: R003 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: THE APPLICATION HAS BEEN REFUSED |
|
18R | Application refused |
Effective date: 20191018 |