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公开(公告)号：US11031002B2
公开(公告)日：2021-06-08
申请号：US16548947
申请日：2019-08-23
申请人： Google LLC
IPC分类号： G10L15/00 , G10L15/20 , G06F3/16 , H03G3/30 , G10L15/22 , G10L17/06 , G10L21/034 , G10L25/84 , G10L17/00 , G10L15/26
摘要： The technology described in this document can be embodied in a computer-implemented method that includes receiving, at a processing system, a first signal including an output of a speaker device and an additional audio signal. The method also includes determining, by the processing system, based at least in part on a model trained to identify the output of the speaker device, that the additional audio signal corresponds to an utterance of a user. The method further includes initiating a reduction in an audio output level of the speaker device based on determining that the additional audio signal corresponds to the utterance of the user.
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公开(公告)号：US20210074280A1
公开(公告)日：2021-03-11
申请号：US17099367
申请日：2020-11-16
申请人： Google LLC
IPC分类号： G10L15/197 , G10L15/00 , G10L15/22 , G10L15/30 , G10L15/08 , G10L15/14 , G10L15/18 , G10L13/00
摘要： Determining a language for speech recognition of a spoken utterance received via an automated assistant interface for interacting with an automated assistant. Implementations can enable multilingual interaction with the automated assistant, without necessitating a user explicitly designate a language to be utilized for each interaction. Implementations determine a user profile that corresponds to audio data that captures a spoken utterance, and utilize language(s), and optionally corresponding probabilities, assigned to the user profile in determining a language for speech recognition of the spoken utterance. Some implementations select only a subset of languages, assigned to the user profile, to utilize in speech recognition of a given spoken utterance of the user. Some implementations perform speech recognition in each of multiple languages assigned to the user profile, and utilize criteria to select only one of the speech recognitions as appropriate for generating and providing content that is responsive to the spoken utterance.
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公开(公告)号：US20210043191A1
公开(公告)日：2021-02-11
申请号：US17046994
申请日：2019-12-02
申请人： Google LLC
摘要： Text independent speaker recognition models can be utilized by an automated assistant to verify a particular user spoke a spoken utterance and/or to identify the user who spoke a spoken utterance. Implementations can include automatically updating a speaker embedding for a particular user based on previous utterances by the particular user. Additionally or alternatively, implementations can include verifying a particular user spoke a spoken utterance using output generated by both a text independent speaker recognition model as well as a text dependent speaker recognition model. Furthermore, implementations can additionally or alternatively include prefetching content for several users associated with a spoken utterance prior to determining which user spoke the spoken utterance.
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公开(公告)号：US10679611B2
公开(公告)日：2020-06-09
申请号：US15973466
申请日：2018-05-07
申请人： Google LLC
摘要： The present disclosure relates generally to determining a language for speech recognition of a spoken utterance, received via an automated assistant interface, for interacting with an automated assistant. The system can enable multilingual interaction with the automated assistant, without necessitating a user explicitly designate a language to be utilized for each interaction. Selection of a speech recognition model for a particular language can based on one or more interaction characteristics exhibited during a dialog session between a user and an automated assistant. Such interaction characteristics can include anticipated user input types, anticipated user input durations, a duration for monitoring for a user response, and/or an actual duration of a provided user response.
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公开(公告)号：US10580401B2
公开(公告)日：2020-03-03
申请号：US14613493
申请日：2015-02-04
申请人： Google LLC
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network. One of the methods includes generating, by a speech recognition system, a matrix from a predetermined quantity of vectors that each represent input for a layer of a neural network, generating a plurality of sub-matrices from the matrix, using, for each of the sub-matrices, the respective sub-matrix as input to a node in the layer of the neural network to determine whether an utterance encoded in an audio signal comprises a keyword for which the neural network is trained.
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公开(公告)号：US10522137B2
公开(公告)日：2019-12-31
申请号：US15956350
申请日：2018-04-18
申请人： Google LLC
发明人： Meltem Oktem , Taral Pradeep Joglekar , Fnu Heryandi , Pu-sen Chao , Ignacio Lopez Moreno , Salil Rajadhyaksha , Alexander H. Gruenstein , Diego Melendo Casado
IPC分类号： G10L15/08 , G06F21/32 , G10L17/06 , G06F16/635 , G06K9/00 , G10L15/07 , G10L17/00 , G10L15/22 , G10L15/26
摘要： In some implementations, authentication tokens corresponding to known users of a device are stored on the device. An utterance from a speaker is received. The utterance is classified as spoken by a particular known user of the known users. A query that includes a representation of the utterance and an indication of the particular known user as the speaker is provided using the authentication token of the particular known user.
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公开(公告)号：US10431213B2
公开(公告)日：2019-10-01
申请号：US15887034
申请日：2018-02-02
申请人： Google LLC
IPC分类号： G10L15/20 , G10L15/22 , H03G3/30 , G10L17/06 , G06F3/16 , G10L21/034 , G10L25/84 , G10L17/00 , G10L15/26
摘要： The technology described in this document can be embodied in a computer-implemented method that includes receiving, at a processing system, a first signal including an output of a speaker device and an additional audio signal. The method also includes determining, by the processing system, based at least in part on a model trained to identify the output of the speaker device, that the additional audio signal corresponds to an utterance of a user. The method further includes initiating a reduction in an audio output level of the speaker device based on determining that the additional audio signal corresponds to the utterance of the user.
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公开(公告)号：US20190287528A1
公开(公告)日：2019-09-19
申请号：US16362831
申请日：2019-03-25
申请人： Google LLC
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for contextual hotwords are disclosed. In one aspect, a method, during a boot process of a computing device, includes the actions of determining, by a computing device, a context associated with the computing device. The actions further include, based on the context associated with the computing device, determining a hotword. The actions further include, after determining the hotword, receiving audio data that corresponds to an utterance. The actions further include determining that the audio data includes the hotword. The actions further include, in response to determining that the audio data includes the hotword, performing an operation associated with the hotword.
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公开(公告)号：US10276161B2
公开(公告)日：2019-04-30
申请号：US15391358
申请日：2016-12-27
申请人： Google LLC
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for contextual hotwords are disclosed. In one aspect, a method, during a boot process of a computing device, includes the actions of determining, by a computing device, a context associated with the computing device. The actions further include, based on the context associated with the computing device, determining a hotword. The actions further include, after determining the hotword, receiving audio data that corresponds to an utterance. The actions further include determining that the audio data includes the hotword. The actions further include, in response to determining that the audio data includes the hotword, performing an operation associated with the hotword.
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公开(公告)号：US20180315430A1
公开(公告)日：2018-11-01
申请号：US15966667
申请日：2018-04-30
申请人： Google LLC
摘要： This document generally describes systems, methods, devices, and other techniques related to speaker verification, including (i) training a neural network for a speaker verification model, (ii) enrolling users at a client device, and (iii) verifying identities of users based on characteristics of the users' voices. Some implementations include a computer-implemented method. The method can include receiving, at a computing device, data that characterizes an utterance of a user of the computing device. A speaker representation can be generated, at the computing device, for the utterance using a neural network on the computing device. The neural network can be trained based on a plurality of training samples that each: (i) include data that characterizes a first utterance and data that characterizes one or more second utterances, and (ii) are labeled as a matching speakers sample or a non-matching speakers sample.
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