-
公开(公告)号:US20210117624A1
公开(公告)日:2021-04-22
申请号:US16998423
申请日:2020-08-20
Applicant: Facebook, Inc.
Inventor: Armen Aghajanyan , Sonal Gupta , Brian Moran , Theodore Frank Levin , Crystal Annette Naomi Su Hua Nakatsu , Daniel Difranco , Jonathan David Christensen , Kirk LaBuda , Anuj Kumar
IPC: G06F40/30 , G06F40/205 , G06F9/54
Abstract: In one embodiment, a method includes receiving a user input comprising a natural-language utterance by an assistant xbot from a client system associated with a user, determining a semantic representation of the user input based on a structural ontology defining a labeling syntax for parsing the natural-language utterance to semantic units comprising actions, objects, and attributes, wherein the semantic representation embeds at least one object within at least one action and declares at least one attribute of the embedded object to be acted upon, sending a request based on the semantic representation to an agent for executing a task corresponding to the user input, receiving results of the executed task mapped to a structure determined by the structural ontology from the agent, and sending from the assistant xbot to the client system instructions for presenting a response based on the results of the executed task.
-
公开(公告)号:US11107462B1
公开(公告)日:2021-08-31
申请号:US16175086
申请日:2018-10-30
Applicant: Facebook, Inc.
Inventor: Christian Fuegen , Yongquiang Wang , Anuj Kumar , Baiyang Liu , Dmitrii Serdiuk
Abstract: Exemplary embodiments relate to improvements in spoken language understanding (SLU) systems. Conventionally, SLU systems include an automatic speech recognition (ASR) component configured to receive an input of audio data and to generate a textual representation of the audio data. Conventional SLU systems also include a natural language understanding (NLU) component configured to receive a text-based transcript and perform language-based tasks such as domain classification, intent determination, and slot-filling. However, these two components are typically trained separately based on different metrics. In real-world situations, errors in the ASR component propagate to the NLU component, which degrades the performance of the overall system. Exemplary embodiments described herein perform SLU in an end-to-end manner that infers semantic meaning directly from audio features without an intermediate text representation. This may allow for more a more accurate translation performed in a more resource-efficient manner (particularly in terms of processing resources).
-
公开(公告)号:US20190325084A1
公开(公告)日:2019-10-24
申请号:US15967290
申请日:2018-04-30
Applicant: Facebook, Inc.
Inventor: Fuchun Peng , Fei Sha , Kun Han , Wenhai Yang , Anuj Kumar , Michael Robert Hanson , Benoit F. Dumoulin
Abstract: In one embodiment, a method includes receiving a user request for a summarization of a particular type of content objects from a client system associated with a first user, determining one or more modalities associated with the user request, selecting a plurality of content objects of the particular type based on a user profile of the first user, wherein the user profile comprises one or more confidence scores associated with one or more subjects associated with the first user, respectively, and wherein the plurality of content objects are selected based on the one or more confidence scores, generating a summary of each content object based on the user profile and the determined modalities, and sending, to the client system in response to the user request, instructions for presenting the summaries of the plurality of content objects, wherein the summaries are presented via one or more of the determined modalities.
-
公开(公告)号:US10452782B1
公开(公告)日:2019-10-22
申请号:US15900703
申请日:2018-02-20
Applicant: Facebook, Inc.
Inventor: Anuj Kumar , Benoit F. Dumoulin
Abstract: Systems, methods, and non-transitory computer-readable media can receive, from a first entity, training data for training an intent model associated with a first intent of a plurality of intents. A first intent model associated with the first intent is generated based on the training data. The first intent model is made available in an intent marketplace for access by a second entity.
-
公开(公告)号:US11086845B1
公开(公告)日:2021-08-10
申请号:US16236369
申请日:2018-12-29
Applicant: Facebook, Inc.
Inventor: Rushin Shah , Anuj Kumar , Ted Li , Wei Chen , Shusen Liu
Abstract: Techniques for database versioning are described. In one embodiment, an apparatus may comprise a database change management component operative to compare a developer table to a reference table to determine a database change set, wherein both the developer table and the reference table are based on a target table; a database conflict management component operative to compare the database change set to the target table to determine a conflicting change set; and a user interface component operative to display the conflicting change set where the conflicting change set comprises one or more conflicting changes; and indicate a conflict-free change set where the conflicting change set is empty. Other embodiments are described and claimed.
-
公开(公告)号:US10963273B2
公开(公告)日:2021-03-30
申请号:US15967290
申请日:2018-04-30
Applicant: Facebook, Inc.
Inventor: Fuchun Peng , Fei Sha , Kun Han , Wenhai Yang , Anuj Kumar , Michael Robert Hanson , Benoit F. Dumoulin
IPC: G06F16/00 , G06F9/451 , G10L15/18 , G10L15/183 , G10L15/22 , G06F16/338 , G06F16/332 , G06F16/33 , G06N20/00 , G06F16/9535 , G06Q50/00 , H04L29/08 , G06F16/176 , G10L15/06 , G10L15/16 , G06F3/01 , G06F16/9032 , G06F16/2457 , H04L12/58 , G06F3/16 , G06K9/00 , G06K9/62 , G06N3/08 , G10L15/26 , G06F16/9038 , G06F16/904 , G06F40/30 , G06F40/40 , G06F16/22 , G06F16/23 , G06F7/14 , H04L12/26 , H04L12/28 , H04L12/24 , H04W12/08 , G10L15/07 , G10L17/22 , G10L13/00 , G10L13/04
Abstract: In one embodiment, a method includes receiving a user request for a summarization of a particular type of content objects from a client system associated with a first user, determining one or more modalities associated with the user request, selecting a plurality of content objects of the particular type based on a user profile of the first user, wherein the user profile comprises one or more confidence scores associated with one or more subjects associated with the first user, respectively, and wherein the plurality of content objects are selected based on the one or more confidence scores, generating a summary of each content object based on the user profile and the determined modalities, and sending, to the client system in response to the user request, instructions for presenting the summaries of the plurality of content objects, wherein the summaries are presented via one or more of the determined modalities.
-
公开(公告)号:US20190327330A1
公开(公告)日:2019-10-24
申请号:US15967239
申请日:2018-04-30
Applicant: Facebook, Inc.
Inventor: Vivek Natarajan , Wenhai Yang , Honglei Liu , Anuj Kumar
Abstract: In one embodiment, a method includes accessing a plurality of content objects associated with a first user from an online social network, accessing a baseline profile, wherein the baseline profile is based on ontology data from one or more information graphs, accessing conversational data associated with the first user, determining one or more subjects associated with the first user based on the plurality of content objects and conversational data associated with the first user, and generating a customized user profile for the first user based on the baseline profile, wherein the user profile comprises one or more confidence scores associated with the respective one or more subjects associated with the first user, wherein the one or more confidence scores are calculated based on the plurality of content objects associated with the first user and the conversational data associated with the first user.
-
公开(公告)号:US20190205386A1
公开(公告)日:2019-07-04
申请号:US16211414
申请日:2018-12-06
Applicant: Facebook, Inc.
Inventor: Anuj Kumar , Benoit Dumoulin , Wenhai Yang , Rajen Subba
CPC classification number: G06F17/2785 , G06F9/453 , G06N5/043 , G06N5/046 , G06N20/00
Abstract: A user interacts with a virtual digital assistant with the intent that it provides assistance with a task. The user sends messages to the virtual digital assistant that include content obtained via user input at a client device. An intent determination model is applied to the content to identify the user's intent. The virtual digital assistant identifies agents that are capable of servicing the intent are identified and retrieves contextual data relating to the message from a data store. An intent arbitration model is used to select one of the agents which is activated to provide assistance with the task. The contextual information may include global metrics of agent performance and/or information regarding the user's preferences.
-
-
-
-
-
-
-