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公开(公告)号：US12056956B2
公开(公告)日：2024-08-06
申请号：US18204785
申请日：2023-06-01
Applicant: GOOGLE LLC
Inventor： Diego Melendo Casado , Tuan Nguyen , Jaclyn Konzelmann , Gustavo Moura , Tanya Kraljic
CPC classification number: G06V40/50 , G06V40/161 , G06V40/70 , G10L17/00 , G10L17/04
Abstract: Techniques are described herein for dialog-based enrollment of individual users for single- and/or multi-modal recognition by an automated assistant, as well as determining how to respond to a particular user's request based on the particular user being enrolled and/or recognized. Rather than requiring operation of a graphical user interface for individual enrollment, dialog-based enrollment enables users to enroll themselves (or others) by way of a human-to-computer dialog with the automated assistant.
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公开(公告)号：US12051416B2
公开(公告)日：2024-07-30
申请号：US18228948
申请日：2023-08-01
Applicant: GOOGLE LLC
Inventor： Lior Alon , Rafael Goldfarb , Dekel Auster , Dan Rasin , Michael Andrew Goodman , Trevor Strohman , Nino Tasca , Valerie Nygaard , Jaclyn Konzelmann
CPC classification number: G10L15/22 , G06F3/167 , G10L15/083 , G10L15/1815 , G10L15/285 , G10L2015/223
Abstract: Implementations described herein relate to reducing latency in automated assistant interactions. In some implementations, a client device can receive audio data that captures a spoken utterance of a user. The audio data can be processed to determine an assistant command to be performed by an automated assistant. The assistant command can be processed, using a latency prediction model, to generate a predicted latency to fulfill the assistant command. Further, the client device (or the automated assistant) can determine, based on the predicted latency, whether to audibly render pre-cached content for presentation to the user prior to audibly rendering content that is responsive to the spoken utterance. The pre-cached content can be tailored to the assistant command and audibly rendered for presentation to the user while the content is being obtained, and the content can be audibly rendered for presentation to the user subsequent to the pre-cached content.
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13.发明公开公开(公告)号：US20240013783A1
公开(公告)日：2024-01-11
申请号：US18244738
申请日：2023-09-11
Applicant: GOOGLE LLC
Inventor： Raunaq Shah , Jaclyn Konzelmann , Lisa Takehana , Ruxandra Davies , Adrian Diaconu
CPC classification number: G10L15/22 , G06F3/167 , G10L2015/221 , G10L2015/223
Abstract: Implementations set forth herein relate to employing dynamic regulations for governing responsiveness of multiple automated assistant devices, and specifically the responsiveness an automated assistant to a given spoken utterance that has been acknowledged by two or more of the assistant devices. The dynamic regulations can be context-dependent and adapted over time in order that the automated assistant can accommodate assistant interaction preferences that may vary from user to user. For instance, a spoken utterance such as “stop,” may be intended to affect different assistant actions based on a context in which the user provided the spoken utterance. The context can refer to a location of the user relative to other rooms in a home, a time of day, a user providing the spoken utterance, an arrangement of the assistant devices within a home, and/or a state of each device in the home.
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公开(公告)号：US20220351720A1
公开(公告)日：2022-11-03
申请号：US17243232
申请日：2021-04-28
Applicant: Google LLC
Inventor： Lior Alon , Rafael Goldfarb , Dekel Auster , Dan Rasin , Michael Andrew Goodman , Trevor Strohman , Nino Tasca , Valerie Nygaard , Jaclyn Konzelmann
Abstract: Implementations described herein relate to reducing latency in automated assistant interactions. In some implementations, a client device can receive audio data that captures a spoken utterance of a user. The audio data can be processed to determine an assistant command to be performed by an automated assistant. The assistant command can be processed, using a latency prediction model, to generate a predicted latency to fulfill the assistant command. Further, the client device (or the automated assistant) can determine, based on the predicted latency, whether to audibly render pre-cached content for presentation to the user prior to audibly rendering content that is responsive to the spoken utterance. The pre-cached content can be tailored to the assistant command and audibly rendered for presentation to the user while the content is being obtained, and the content can be audibly rendered for presentation to the user subsequent to the pre-cached content.
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公开(公告)号：US11373649B2
公开(公告)日：2022-06-28
申请号：US16622112
申请日：2018-08-21
Applicant: Google LLC
Inventor： Diego Melendo Casado , Jaclyn Konzelmann
Abstract: Techniques are described herein for enabling the use of “dynamic” or “context-specific” hot words for an automated assistant. In various implementations, an automated assistant may be operated at least in part on a computing device. Audio data captured by a microphone may be monitored for default hot word(s). Detection of one or more of the default hot words may trigger transition of the automated assistant from a limited hot word listening state into a speech recognition state. Transition of the computing device into a given state may be detected, and in response, the audio data captured by the microphone may be monitored for context-specific hot word(s), in addition to or instead of the default hot word(s). Detection of the context-specific hot word(s) may trigger the automated assistant to perform a responsive action associated with the given state, without requiring detection of default hot word(s).
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Patent Agency Ranking
公开(公告)号：US11238142B2
公开(公告)日：2022-02-01
申请号：US16403532
申请日：2019-05-04
Applicant: Google LLC
Inventor： Diego Melendo Casado , Tuan Nguyen , Jaclyn Konzelmann
Abstract: Techniques are described herein for dialog-based enrollment of individual users for single- and/or multi-modal recognition by an automated assistant, as well as determining how to respond to a particular user's request based on the particular user being enrolled and/or recognized. Rather than requiring operation of a graphical user interface for individual enrollment, dialog-based enrollment enables users to enroll themselves (or others) by way of a human-to-computer dialog with the automated assistant.
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公开(公告)号：US12170816B2
公开(公告)日：2024-12-17
申请号：US18234771
申请日：2023-08-16
Applicant: GOOGLE LLC
Inventor： Jaclyn Konzelmann , Tuan Nguyen , Vinay Bettadapura , Andrew Gallagher , Utsav Prabhu , Caroline Pantofaru
IPC: H04N21/442 , G06T7/70 , H04N21/258 , H04N21/41 , H04W12/64
Abstract: Implementations relate to an automated assistant that provides and manages output from one or more elements of output hardware of a computing device. The automated assistant manages dynamic adjustment of access permissions to the computing device according to, for example, a detected presence of one or more users. An active-user queue can be established each time a unique user enters a viewing window of a camera of the computing device when, up to that point, no user was considered active. Multiple image frames can be captured via the camera and processed to determine whether an initial user remains in the viewing window and/or whether another user has entered the viewing window. The initial user can be considered active as long as they are exclusively detected in the viewing window. Restricted content associated with the user may be rendered by the computing device whilst the user is active.
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公开(公告)号：US20240346851A1
公开(公告)日：2024-10-17
申请号：US18750561
申请日：2024-06-21
Applicant: GOOGLE LLC
Inventor： Diego Melendo Casado , Tuan Nguyen , Jaclyn Konzelmann , Gustavo Moura , Tanya Kraljic
CPC classification number: G06V40/50 , G06V40/161 , G06V40/70 , G10L17/00 , G10L17/04
Abstract: Techniques are described herein for dialog-based enrollment of individual users for single-and/or multi-modal recognition by an automated assistant, as well as determining how to respond to a particular user's request based on the particular user being enrolled and/or recognized. Rather than requiring operation of a graphical user interface for individual enrollment, dialog-based enrollment enables users to enroll themselves (or others) by way of a human-to-computer dialog with the automated assistant.
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公开(公告)号：US20240320445A1
公开(公告)日：2024-09-26
申请号：US18675840
申请日：2024-05-28
Applicant: GOOGLE LLC
Inventor： Shrestha Basu Mallick , Owen Lewis , Jaclyn Konzelmann , Christina Yang Choi , James Freedman , Jonathan Malmaud , Xin Xie , Brian Carver
IPC: G06F40/40
CPC classification number: G06F40/40
Abstract: Implementations described herein relate to attribution of a natural language (NL) based summary generated using a large language model (LLM). Processor(s) of a system can: receive NL based input associated with a client device, generate the NL based summary using the LLM, and process the NL based summary to determine whether a NL based summary segment of the NL based summary matches a dataset segment of a dataset that was utilized to initially train the LLM and/or to fine-tune the LLM. Further, the processor(s) can, in response to determining that the NL based summary segment matches the dataset segment, modify the NL based summary segment of the NL based summary to generate a modified NL based summary. Moreover, the processor(s) can cause the modified NL based summary to be rendered at the client device. The attribution of the NL based summary can be provided as a service to various third-parties.
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20.发明授权公开(公告)号：US12087300B2
公开(公告)日：2024-09-10
申请号：US18244738
申请日：2023-09-11
Applicant: GOOGLE LLC
Inventor： Raunaq Shah , Jaclyn Konzelmann , Lisa Takehana , Ruxandra Davies , Adrian Diaconu
CPC classification number: G10L15/22 , G06F3/167 , G10L2015/221 , G10L2015/223
Abstract: Implementations set forth herein relate to employing dynamic regulations for governing responsiveness of multiple automated assistant devices, and specifically the responsiveness an automated assistant to a given spoken utterance that has been acknowledged by two or more of the assistant devices. The dynamic regulations can be context-dependent and adapted over time in order that the automated assistant can accommodate assistant interaction preferences that may vary from user to user. For instance, a spoken utterance such as “stop,” may be intended to affect different assistant actions based on a context in which the user provided the spoken utterance. The context can refer to a location of the user relative to other rooms in a home, a time of day, a user providing the spoken utterance, an arrangement of the assistant devices within a home, and/or a state of each device in the home.
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