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公开(公告)号：US20240193372A1
公开(公告)日：2024-06-13
申请号：US18064230
申请日：2022-12-09
申请人： Google LLC
CPC分类号： G06F40/35 , G06N20/00 , G06Q30/0281
摘要： A method for dynamically generating training data for a model includes receiving a transcript corresponding to a conversation between a customer and an agent, the transcript comprising a customer input and an agent input. The method includes receiving a logic model including a plurality of responses, each response of the plurality of responses representing a potential reply to the customer input. The method further includes selecting, based on the agent input, a response from the plurality of responses of the logic model. The method includes determining that a similarity score between the selected response and the agent input satisfies a similarity threshold, and, based on determining that the similarity score between the selected response and the agent input satisfies the similarity threshold, training a machine learning model using the customer input and the selected response.
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公开(公告)号：US20240112679A1
公开(公告)日：2024-04-04
申请号：US18540377
申请日：2023-12-14
申请人： GOOGLE LLC
IPC分类号： G10L15/22 , G06F16/903 , G06N3/006 , G10L15/18
CPC分类号： G10L15/22 , G06F16/90335 , G06N3/006 , G10L15/1815 , G10L15/1822 , G10L2015/223
摘要： Methods, apparatus, and computer readable media are described related to automated assistants that proactively incorporate, into human-to-computer dialog sessions, unsolicited content of potential interest to a user. In various implementations, in an existing human-to-computer dialog session between a user and an automated assistant, it may be determined that the automated assistant has responded to all natural language input received from the user. Based on characteristic(s) of the user, information of potential interest to the user or action(s) of potential interest to the user may be identified. Unsolicited content indicative of the information of potential interest to the user or the action(s) may be generated and incorporated by the automated assistant into the existing human-to-computer dialog session. In various implementations, the incorporating may be performed in response to the determining that the automated assistant has responded to all natural language input received from the user during the human-to-computer dialog session.
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公开(公告)号：US11908462B2
公开(公告)日：2024-02-20
申请号：US17699580
申请日：2022-03-21
申请人： Google LLC
CPC分类号： G10L15/1815 , G06F3/167 , G06F40/30 , G10L15/1822 , G10L15/22 , G10L2015/223 , G10L2015/226
摘要： The systems and methods of the present disclosure generally relate to a data processing system that can identify and surface alternative requests when presented with ambiguous, unclear, or other requests to which a data processing system may not be able to respond. The data processing system can improve the efficiency of network transmissions to reduce network bandwidth usage and processor utilization by selecting alternative requests that are responsive to the intent of the original request.
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公开(公告)号：US11887592B2
公开(公告)日：2024-01-30
申请号：US17411532
申请日：2021-08-25
申请人： Google LLC
发明人： Vladimir Vuskovic , Stephan Wenger , Zineb Ait Bahajji , Martin Baeuml , Alexandru Dovlecel , Gleb Skobeltsyn
IPC分类号： G10L15/22 , G06F40/35 , G06F40/56 , G06F40/295 , G10L15/18
CPC分类号： G10L15/22 , G06F40/295 , G06F40/35 , G06F40/56 , G10L15/1815 , G10L15/222 , G10L2015/227
摘要： Methods, apparatus, and computer readable media are described related to automated assistants that proactively incorporate, into human-to-computer dialog sessions, unsolicited content of potential interest to a user. In various implementations, based on content of an existing human-to-computer dialog session between a user and an automated assistant, an entity mentioned by the user or automated assistant may be identified. Fact(s)s related to the entity or to another entity that is related to the entity may be identified based on entity data contained in database(s). For each of the fact(s), a corresponding measure of potential interest to the user may be determined. Unsolicited natural language content may then be generated that includes one or more of the facts selected based on the corresponding measure(s) of potential interest. The automated assistant may then incorporate the unsolicited content into the existing human-to-computer dialog session or a subsequent human-to-computer dialog session.
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公开(公告)号：US11615124B2
公开(公告)日：2023-03-28
申请号：US17116296
申请日：2020-12-09
申请人： Google LLC
IPC分类号： G06F16/332 , G06F16/33
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating subqueries from a query. In one aspect, a method includes obtaining a query, generating a set of two subqueries from the query, where the set includes a first subquery and a second subquery, determining a quality score for the set of two subqueries, determining whether the quality score for the set of two subqueries satisfies a quality threshold, and in response to determining that the quality score for the set of two subqueries satisfies the quality threshold, providing a first response to the first subquery that is responsive to a first operation that receives the first subquery as input and providing a second response to the second subquery that is responsive to a second operation that receives the second subquery as input.
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公开(公告)号：US11438185B2
公开(公告)日：2022-09-06
申请号：US16927373
申请日：2020-07-13
申请人： Google LLC
发明人： Vladimir Vuskovic , Yariv Adan
IPC分类号： H04L12/18 , H04L51/02 , G06F16/00 , G06F40/40 , G06Q10/00 , H04L51/216 , H04L67/75 , H04L65/4038 , G06Q10/06
摘要： Techniques are described herein for automated assistants that proactively provide content to participant(s) of multi-participant message exchange threads (e.g., group chats, audio and/or video calls in which oral messages are transcribed for analysis, etc.) based on signals such as individual participant profiles associated with participant(s). In various implementations, automated assistant(s) that may not be explicitly invoked may analyze content of a message exchange thread involving multiple human participants and/or document(s) associated with the message exchange thread. Based on the analyzing, the automated assistant(s) may identify topic(s) pertinent to the message exchange thread. Based on individual participant profiles associated with the participants, the automated assistant(s) may identify shared interest(s) of the participants. The automated assistant(s) may then select new content based both on the pertinent topic(s) and the shared interest(s) of the participants and proactively provide the new content to one or more of the participants.
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公开(公告)号：US20220208183A1
公开(公告)日：2022-06-30
申请号：US17699580
申请日：2022-03-21
申请人： Google LLC
摘要： The systems and methods of the present disclosure generally relate to a data processing system that can identify and surface alternative requests when presented with ambiguous, unclear, or other requests to which a data processing system may not be able to respond. The data processing system can improve the efficiency of network transmissions to reduce network bandwidth usage and processor utilization by selecting alternative requests that are responsive to the intent of the original request.
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8.发明申请公开(公告)号：US20220157308A1
公开(公告)日：2022-05-19
申请号：US17587478
申请日：2022-01-28
申请人： Google LLC
发明人： Michael Fink , Vladimir Vuskovic , Shimon Or Salant , Deborah Cohen , Asaf Revach , David Kogan , Andrew Callahan , Richard Borovoy , Andrew Richardson , Eran Ofek , Idan Szpektor , Jonathan Berant , Yossi Matias
摘要： Generating expanded responses that guide continuance of a human-to computer dialog that is facilitated by a client device and that is between at least one user and an automated assistant. The expanded responses are generated by the automated assistant in response to user interface input provided by the user via the client device, and are caused to be rendered to the user via the client device, as a response, by the automated assistant, to the user interface input of the user. An expanded response is generated based on at least one entity of interest determined based on the user interface input, and is generated to incorporate content related to one or more additional entities that are related to the entity of interest, but that are not explicitly referenced by the user interface input.
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公开(公告)号：US11048995B2
公开(公告)日：2021-06-29
申请号：US15847341
申请日：2017-12-19
申请人： Google LLC
发明人： Yariv Adan , Vladimir Vuskovic , Behshad Behzadi
IPC分类号： G06N3/00 , G06Q10/06 , G10L15/22 , G06Q10/02 , G06F3/16 , G06F16/332 , G10L13/00 , H04M3/493
摘要： An example method includes receiving, by a computational assistant executing at one or more processors, a representation of an utterance spoken at a computing device; identifying, based on the utterance, a task to be performed by the computational assistant; responsive to determining, by the computational assistant, that complete performance of the task will take more than a threshold amount of time, outputting, for playback by one or more speakers operably connected to the computing device, synthesized voice data that informs a user of the computing device that complete performance of the task will not be immediate; and performing, by the computational assistant, the task.
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10.发明授权公开(公告)号：US12118998B2
公开(公告)日：2024-10-15
申请号：US18231112
申请日：2023-08-07
申请人： GOOGLE LLC
发明人： Mugurel Ionut Andreica , Vladimir Vuskovic , Joseph Lange , Sharon Stovezky , Marcin Nowak-Przygodzki
CPC分类号： G10L15/22 , G06N3/08 , G10L15/02 , G10L2015/223
摘要： Implementations are set forth herein for creating an order of execution for actions that were requested by a user, via a spoken utterance to an automated assistant. The order of execution for the requested actions can be based on how each requested action can, or is predicted to, affect other requested actions. In some implementations, an order of execution for a series of actions can be determined based on an output of a machine learning model, such as a model that has been trained according to supervised learning. A particular order of execution can be selected to mitigate waste of processing, memory, and network resources—at least relative to other possible orders of execution. Using interaction data that characterizes past performances of automated assistants, certain orders of execution can be adapted over time, thereby allowing the automated assistant to learn from past interactions with one or more users.
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