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公开(公告)号：US20220130385A1
公开(公告)日：2022-04-28
申请号：US17569811
申请日：2022-01-06
Applicant: GOOGLE LLC
Inventor： Lucas Mirelmann , Zaheed Sabur , Bohdan Vlasyuk , Marie Patriarche Bledowski , Sergey NAZAROV , Denis Burakov , Behshad Behzadi , Michael Golikov , Steve CHENG , Daniel Cotting , Mario Bertschler
Abstract: Implementations herein relate to pre-caching data, corresponding to predicted interactions between a user and an automated assistant, using data characterizing previous interactions between the user and the automated assistant. An interaction can be predicted based on details of a current interaction between the user and an automated assistant. One or more predicted interactions can be initialized, and/or any corresponding data pre-cached, prior to the user commanding the automated assistant in furtherance of the predicted interaction. Interaction predictions can be generated using a user-parameterized machine learning model, which can be used when processing input(s) that characterize a recent user interaction with the automated assistant. Should the user command the automated assistant in a way that is aligned with a pre-cached, predicted interaction, the automated assistant will exhibit instant fulfillment of the command, thereby eliminating any latency that the user would have otherwise experienced interacting with the automated assistant.
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公开(公告)号：US20240272970A1
公开(公告)日：2024-08-15
申请号：US18648842
申请日：2024-04-29
Applicant: GOOGLE LLC
Inventor： Bohdan Vlasyuk , Behshad Behzadi , Mario Bertschler , Denis Burakov , Daniel Cotting , Michael Golikov , Lucas Mirelmann , Steve Cheng , Sergey Nazarov , Zaheed Sabur , Jonathan Lee , Lucia Terrenghi , Adrian Zumbrunnen
CPC classification number: G06F9/547 , G06F3/167 , G06F40/166 , G06F40/35 , G10L15/22 , G10L15/26 , G10L2015/223
Abstract: Implementations set forth herein relate to an automated assistant that can be invoked while a user is interfacing with a foreground application in order to retrieve data from one or more different applications, and then provide the retrieved data to the foreground application. A user can invoke the automated assistant while operating the foreground application by providing a spoken utterance, and the automated assistant can select one or more other applications to query based on content of the spoken utterance. Application data collected by the automated assistant from the one or more other applications can then be used to provide an input to the foreground application. In this way, the user can bypass switching between applications in the foreground in order to retrieve data that has been generated by other applications.
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公开(公告)号：US12057119B2
公开(公告)日：2024-08-06
申请号：US18092883
申请日：2023-01-03
Applicant: GOOGLE LLC
Inventor： Victor Carbune , Matthew Sharifi , Ondrej Skopek , Justin Lu , Daniel Valcarce , Kevin Kilgour , Mohamad Hassan Rom , Nicolo D'Ercole , Michael Golikov
CPC classification number: G10L15/22 , G10L15/05 , G10L15/1815 , G10L25/78 , G10L2015/088 , G10L2015/223
Abstract: Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.
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14.发明公开公开(公告)号：US20240185857A1
公开(公告)日：2024-06-06
申请号：US18439411
申请日：2024-02-12
Applicant: GOOGLE LLC
Inventor： Denis Burakov , Behshad Behzadi , Mario Bertschlewr , Bohdan Vlasyuk , Daniel Cotting , Michael Golikov , Lucas Mirelmann , Steve Cheng , Sergey Nazarov , Zaheed Sabur , Marcin Nowak-Przygodzki , Mugurel Ionut Andreica , Radu Voroneanu
CPC classification number: G10L15/26 , G06F3/167 , G10L15/22 , G10L2015/223
Abstract: Implementations set forth herein relate to a system that employs an automated assistant to further interactions between a user and another application, which can provide the automated assistant with permission to initialize relevant application actions simultaneous to the user interacting with the other application. Furthermore, the system can allow the automated assistant to initialize actions of different applications, despite being actively operating a particular application. Available actions can be gleaned by the automated assistant using various application-specific schemas, which can be compared with incoming requests from a user to the automated assistant. Additional data, such as context and historical interactions, can also be used to rank and identify a suitable application action to be initialized via the automated assistant.
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公开(公告)号：US20230143177A1
公开(公告)日：2023-05-11
申请号：US18092883
申请日：2023-01-03
Applicant: GOOGLE LLC
Inventor： Victor Carbune , Matthew Sharifi , Ondrej Skopek , Justin Lu , Daniel Valcarce , Kevin Kilgour , Mohamad Hassan Rom , Nicolo D'Ercole , Michael Golikov
CPC classification number: G10L15/22 , G10L15/05 , G10L15/1815 , G10L25/78 , G10L2015/088
Abstract: Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.
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Patent Agency Ranking
公开(公告)号：US20220366903A1
公开(公告)日：2022-11-17
申请号：US17321994
申请日：2021-05-17
Applicant: GOOGLE LLC
Inventor： Victor Carbune , Matthew Sharifi , Ondrej Skopek , Justin Lu , Daniel Valcarce , Kevin Kilgour , Mohamad Hassan Rom , Nicolo D'Ercole , Michael Golikov
Abstract: Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.
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公开(公告)号：US20220157317A1
公开(公告)日：2022-05-19
申请号：US17588481
申请日：2022-01-31
Applicant: Google LLC
Inventor： Denis Burakov , Behshad Behzadi , Mario Bertschler , Bohdan Vlasyuk , Daniel Cotting , Michael Golikov , Lucas Mirelmann , Steve Cheng , Sergey NAZAROV , Zaheed Sabur , Marcin Nowak-Przygodzki , Mugurel Ionut Andreica , Radu Voroneanu
Abstract: Implementations set forth herein relate to a system that employs an automated assistant to further interactions between a user and another application, which can provide the automated assistant with permission to initialize relevant application actions simultaneous to the user interacting with the other application. Furthermore, the system can allow the automated assistant to initialize actions of different applications, despite being actively operating a particular application. Available actions can be gleaned by the automated assistant using various application-specific schemas, which can be compared with incoming requests from a user to the automated assistant. Additional data, such as context and historical interactions, can also be used to rank and identify a suitable application action to be initialized via the automated assistant.
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公开(公告)号：US11222637B2
公开(公告)日：2022-01-11
申请号：US16613705
申请日：2019-05-31
Applicant: Google LLC
Inventor： Lucas Mirelmann , Zaheed Sabur , Bohdan Vlasyuk , Marie Patriarche Bledowski , Sergey Nazarov , Denis Burakov , Behshad Behzadi , Michael Golikov , Steve Cheng , Daniel Cotting , Mario Bertschler
Abstract: Implementations herein relate to pre-caching data, corresponding to predicted interactions between a user and an automated assistant, using data characterizing previous interactions between the user and the automated assistant. An interaction can be predicted based on details of a current interaction between the user and an automated assistant. One or more predicted interactions can be initialized, and/or any corresponding data pre-cached, prior to the user commanding the automated assistant in furtherance of the predicted interaction. Interaction predictions can be generated using a user-parameterized machine learning model, which can be used when processing input(s) that characterize a recent user interaction with the automated assistant. Should the user command the automated assistant in a way that is aligned with a pre-cached, predicted interaction, the automated assistant will exhibit instant fulfillment of the command, thereby eliminating any latency that the user would have otherwise experienced interacting with the automated assistant.
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公开(公告)号：US12106759B2
公开(公告)日：2024-10-01
申请号：US17588481
申请日：2022-01-31
Applicant: Google LLC
Inventor： Denis Burakov , Behshad Behzadi , Mario Bertschler , Bohdan Vlasyuk , Daniel Cotting , Michael Golikov , Lucas Mirelmann , Steve Cheng , Sergey Nazarov , Zaheed Sabur , Marcin Nowak-Przygodzki , Mugurel Ionut Andreica , Radu Voroneanu
CPC classification number: G10L15/26 , G06F3/167 , G10L15/22 , G10L2015/223
Abstract: Implementations set forth herein relate to a system that employs an automated assistant to further interactions between a user and another application, which can provide the automated assistant with permission to initialize relevant application actions simultaneous to the user interacting with the other application. Furthermore, the system can allow the automated assistant to initialize actions of different applications, despite being actively operating a particular application. Available actions can be gleaned by the automated assistant using various application-specific schemas, which can be compared with incoming requests from a user to the automated assistant. Additional data, such as context and historical interactions, can also be used to rank and identify a suitable application action to be initialized via the automated assistant.
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公开(公告)号：US20240312461A1
公开(公告)日：2024-09-19
申请号：US18674509
申请日：2024-05-24
Applicant: GOOGLE LLC
Inventor： Lucas Mirelmann , Zaheed Sabur , Bohdan Vlasyuk , Marie Patriarche Bledowski , Sergey Nazarov , Denis Burakov , Behshad Behzadi , Michael Golikov , Steve Cheng , Daniel Cotting , Mario Bertschler
CPC classification number: G10L15/22 , G10L15/083
Abstract: Implementations relate to receiving natural language input that requests an automated assistant to provide information and processing the natural language input to identify the requested information and to identify one or more predicted actions. Those implementations further cause a computing device, at which the natural language input is received, to render the requested information and the one or more predicted actions in response to the natural language input. Yet further, those implementations, in response to the user confirming a rendered predicted action, cause the automated assistant to initialize the predicted action.
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