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公开(公告)号：US20220366914A1
公开(公告)日：2022-11-17
申请号：US17302926
申请日：2021-05-16
Applicant: Google LLC
Inventor： Ignacio Lopez Moreno , Quan Wang , Jason Pelecanos , Yiling Huang , Mert Saglam
IPC: G10L17/06 , G10L17/18 , G10L17/04 , G06F16/245 , G06N3/08
Abstract: A speaker verification method includes receiving audio data corresponding to an utterance, processing the audio data to generate a reference attentive d-vector representing voice characteristics of the utterance, the evaluation ad-vector includes ne style classes each including a respective value vector concatenated with a corresponding routing vector. The method also includes generating using a self-attention mechanism, at least one multi-condition attention score that indicates a likelihood that the evaluation ad-vector matches a respective reference ad-vector associated with a respective user. The method also includes identifying the speaker of the utterance as the respective user associated with the respective reference ad-vector based on the multi-condition attention score.
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公开(公告)号：US20220122614A1
公开(公告)日：2022-04-21
申请号：US17076743
申请日：2020-10-21
Applicant: Google LLC
Inventor： Jason Pelecanos , Pu-sen Chao , Yiling Huang , Quan Wang
Abstract: A method for evaluating a verification model includes receiving a first and a second set of verification results where each verification result indicates whether a primary model or an alternative model verifies an identity of a user as a registered user. The method further includes identifying each verification result in the first and second sets that includes a performance metric. The method also includes determining a first score of the primary model based on a number of the verification results identified in the first set that includes the performance metric and determining a second score of the alternative model based on a number of the verification results identified in the second set that includes the performance metric. The method further includes determining whether a verification capability of the alternative model is better than a verification capability of the primary model based on the first score and the second score.
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公开(公告)号：US12154574B2
公开(公告)日：2024-11-26
申请号：US18506105
申请日：2023-11-09
Applicant: Google LLC
Inventor： Jason Pelecanos , Pu-sen Chao , Yiling Huang , Quan Wang
Abstract: A method for evaluating a verification model includes receiving a first and a second set of verification results where each verification result indicates whether a primary model or an alternative model verifies an identity of a user as a registered user. The method further includes identifying each verification result in the first and second sets that includes a performance metric. The method also includes determining a first score of the primary model based on a number of the verification results identified in the first set that includes the performance metric and determining a second score of the alternative model based on a number of the verification results identified in the second set that includes the performance metric. The method further includes determining whether a verification capability of the alternative model is better than a verification capability of the primary model based on the first score and the second score.
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公开(公告)号：US11837238B2
公开(公告)日：2023-12-05
申请号：US17076743
申请日：2020-10-21
Applicant: Google LLC
Inventor： Jason Pelecanos , Pu-sen Chao , Yiling Huang , Quan Wang
Abstract: A method for evaluating a verification model includes receiving a first and a second set of verification results where each verification result indicates whether a primary model or an alternative model verifies an identity of a user as a registered user. The method further includes identifying each verification result in the first and second sets that includes a performance metric. The method also includes determining a first score of the primary model based on a number of the verification results identified in the first set that includes the performance metric and determining a second score of the alternative model based on a number of the verification results identified in the second set that includes the performance metric. The method further includes determining whether a verification capability of the alternative model is better than a verification capability of the primary model based on the first score and the second score.
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Patent Agency Ranking
公开(公告)号：US20240079013A1
公开(公告)日：2024-03-07
申请号：US18506105
申请日：2023-11-09
Applicant: Google LLC
Inventor： Jason Pelecanos , Pu-sen Chao , Yiling Huang , Quan Wang
Abstract: A method for evaluating a verification model includes receiving a first and a second set of verification results where each verification result indicates whether a primary model or an alternative model verifies an identity of a user as a registered user. The method further includes identifying each verification result in the first and second sets that includes a performance metric. The method also includes determining a first score of the primary model based on a number of the verification results identified in the first set that includes the performance metric and determining a second score of the alternative model based on a number of the verification results identified in the second set that includes the performance metric. The method further includes determining whether a verification capability of the alternative model is better than a verification capability of the primary model based on the first score and the second score.
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公开(公告)号：US11798562B2
公开(公告)日：2023-10-24
申请号：US17302926
申请日：2021-05-16
Applicant: Google LLC
Inventor： Ignacio Lopez Moreno , Quan Wang , Jason Pelecanos , Yiling Huang , Mert Saglam
IPC: G10L17/06 , G06N3/08 , G10L17/04 , G10L17/18 , G06F16/245
CPC classification number: G10L17/06 , G06F16/245 , G06N3/08 , G10L17/04 , G10L17/18
Abstract: A speaker verification method includes receiving audio data corresponding to an utterance, processing the audio data to generate a reference attentive d-vector representing voice characteristics of the utterance, the evaluation ad-vector includes ne style classes each including a respective value vector concatenated with a corresponding routing vector. The method also includes generating using a self-attention mechanism, at least one multi-condition attention score that indicates a likelihood that the evaluation ad-vector matches a respective reference ad-vector associated with a respective user. The method also includes identifying the speaker of the utterance as the respective user associated with the respective reference ad-vector based on the multi-condition attention score.
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公开(公告)号：US20240135934A1
公开(公告)日：2024-04-25
申请号：US18483492
申请日：2023-10-09
Applicant: Google LLC
Inventor： Guanlong Zhao , Quan Wang , Han Lu , Yiling Huang , Jason Pelecanos
Abstract: A method includes obtaining a multi-utterance training sample that includes audio data characterizing utterances spoken by two or more different speakers and obtaining ground-truth speaker change intervals indicating time intervals in the audio data where speaker changes among the two or more different speakers occur. The method also includes processing the audio data to generate a sequence of predicted speaker change tokens using a sequence transduction model. For each corresponding predicted speaker change token, the method includes labeling the corresponding predicted speaker change token as correct when the predicted speaker change token overlaps with one of the ground-truth speaker change intervals. The method also includes determining a precision metric of the sequence transduction model based on a number of the predicted speaker change tokens labeled as correct and a total number of the predicted speaker change tokens in the sequence of predicted speaker change tokens.
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公开(公告)号：US20240029742A1
公开(公告)日：2024-01-25
申请号：US18479615
申请日：2023-10-02
Applicant: Google LLC
Inventor： Ignacio Lopez Moreno , Quan Wang , Jason Pelecanos , Yiling Huang , Mert Saglam
IPC: G10L17/06 , G06F16/245 , G06N3/08 , G10L17/04 , G10L17/18
CPC classification number: G10L17/06 , G06F16/245 , G06N3/08 , G10L17/04 , G10L17/18
Abstract: A speaker verification method includes receiving audio data corresponding to an utterance, processing the audio data to generate a reference attentive d-vector representing voice characteristics of the utterance, the evaluation ad-vector includes ne style classes each including a respective value vector concatenated with a corresponding routing vector. The method also includes generating using a self-attention mechanism, at least one multi-condition attention score that indicates a likelihood that the evaluation ad-vector matches a respective reference ad-vector associated with a respective user. The method also includes identifying the speaker of the utterance as the respective user associated with the respective reference ad-vector based on the multi-condition attention score.
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公开(公告)号：US20230260521A1
公开(公告)日：2023-08-17
申请号：US18167815
申请日：2023-02-10
Applicant: Google LLC
Inventor： Alanna Foster Slocum , Yiling Huang , Shelly Bensal , Quan Wang
Abstract: A method includes obtaining a speaker identification (SID) model trained to predict speaker embeddings from utterances spoken by different speakers, the SID model includes a trained audio encoder and a trained SID head. The method also includes receiving a plurality of synthetic speech detection (SSD) training utterances that include a set of human-originated speech samples and a set of synthetic speech samples. The method also includes training, using the trained audio encoder, a SSD head on the SSD training utterances to learn to detect the presence of synthetic speech in audio encodings encoded by the trained audio encoder. The operations also include providing, for execution on a computing device, a multitask neural network model for performing both SID tasks and SSD tasks on input audio data in parallel.
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