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公开(公告)号：US20200066271A1
公开(公告)日：2020-02-27
申请号：US16527487
申请日：2019-07-31
Applicant: Google LLC
Inventor： Wei Li , Rohit Prakash Prabhavalkar , Kanury Kanishka Rao , Yanzhang He , Ian C. McGraw , Anton Bakhtin
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting utterances of a key phrase in an audio signal. One of the methods includes receiving, by a key phrase spotting system, an audio signal encoding one or more utterances; while continuing to receive the audio signal, generating, by the key phrase spotting system, an attention output using an attention mechanism that is configured to compute the attention output based on a series of encodings generated by an encoder comprising one or more neural network layers; generating, by the key phrase spotting system and using attention output, output that indicates whether the audio signal likely encodes the key phrase; and providing, by the key phrase spotting system, the output that indicates whether the audio signal likely encodes the key phrase.
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公开(公告)号：US12051407B2
公开(公告)日：2024-07-30
申请号：US17815049
申请日：2022-07-26
Applicant: Google LLC
Inventor： Rohit Prakash Prabhavalkar , Golan Pundak , Tara N. Sainath
Abstract: A method includes receiving audio data encoding an utterance and obtaining a set of bias phrases corresponding to a context of the utterance. Each bias phrase includes one or more words. The method also includes processing, using a speech recognition model, acoustic features derived from the audio to generate an output from the speech recognition model. The speech recognition model includes a first encoder configured to receive the acoustic features, a bias encoder configured to receive data indicating the obtained set of bias phrases, a bias encoder, and a decoder configured to determine likelihoods of sequences of speech elements based on output of the first attention module and output of the bias attention module. The method also includes determining a transcript for the utterance based on the likelihoods of sequences of speech elements.
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公开(公告)号：US20240028829A1
公开(公告)日：2024-01-25
申请号：US18346232
申请日：2023-07-01
Applicant: Google LLC
Inventor： Tara N. Sainath , Zhouyuan Huo , Zhehuai Chen , Yu Zhang , Weiran Wang , Trevor Strohman , Rohit Prakash Prabhavalkar , Bo Li , Ankur Bapna
IPC: G06F40/284 , G06F40/40
CPC classification number: G06F40/284 , G06F40/40
Abstract: A method includes receiving training data that includes a set of unspoken textual utterances. For each respective unspoken textual utterance, the method includes, tokenizing the respective textual utterance into a sequence of sub-word units, generating a first higher order textual feature representation for a corresponding sub-word unit tokenized from the respective unspoken textual utterance, receiving the first higher order textual feature representation generated by a text encoder, and generating a first probability distribution over possible text units. The method also includes training an encoder based on the first probability distribution over possible text units generated by a first-pass decoder for each respective unspoken textual utterance in the set of unspoken textual utterances.
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公开(公告)号：US20230298570A1
公开(公告)日：2023-09-21
申请号：US18187222
申请日：2023-03-21
Applicant: Google LLC
Inventor： Weiran Wang , Tongzhou Chen , Tara N. Sainath , Ehsan Variani , Rohit Prakash Prabhavalkar , Ronny Huang , Bhuvana Ramabhadran , Neeraj Gaur , Sepand Mavandadi , Charles Caleb Peyser , Trevor Strohman , Yangzhang He , David Rybach
CPC classification number: G10L15/063 , G10L15/19 , G10L15/22 , G10L15/16 , G10L15/02
Abstract: A method includes generating, using an audio encoder, a higher-order feature representation for each acoustic frame in a sequence of acoustic frames; generating, using a decoder, based on the higher-order feature representation, a plurality of speech recognition hypotheses, each hypotheses corresponding to a candidate transcription of an utterance and having an associated first likelihood score; generating, using an external language model, for each speech recognition hypothesis, a second likelihood score; determining, using a learnable fusion module, for each speech recognition hypothesis, a set of fusion weights based on the higher-order feature representation and the speech recognition hypothesis; and generating, using the learnable fusion module, for each speech recognition hypothesis, a third likelihood score based on the first likelihood score, the second likelihood score, and the set of fusion weights, the audio encoder and decoder trained using minimum additive error rate training in the presence of the external language model.
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公开(公告)号：US11646019B2
公开(公告)日：2023-05-09
申请号：US17443557
申请日：2021-07-27
Applicant: Google LLC
Inventor： Rohit Prakash Prabhavalkar , Tara N. Sainath , Yonghui Wu , Patrick An Phu Nguyen , Zhifeng Chen , Chung-Cheng Chiu , Anjuli Patricia Kannan
IPC: G10L15/197 , G10L15/16 , G10L15/06 , G10L15/02 , G10L15/22
CPC classification number: G10L15/197 , G10L15/02 , G10L15/063 , G10L15/16 , G10L15/22 , G10L2015/025
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-readable storage media, for speech recognition using attention-based sequence-to-sequence models. In some implementations, audio data indicating acoustic characteristics of an utterance is received. A sequence of feature vectors indicative of the acoustic characteristics of the utterance is generated. The sequence of feature vectors is processed using a speech recognition model that has been trained using a loss function that uses N-best lists of decoded hypotheses, the speech recognition model including an encoder, an attention module, and a decoder. The encoder and decoder each include one or more recurrent neural network layers. A sequence of output vectors representing distributions over a predetermined set of linguistic units is obtained. A transcription for the utterance is obtained based on the sequence of output vectors. Data indicating the transcription of the utterance is provided.
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Patent Agency Ranking
公开(公告)号：US20230038343A1
公开(公告)日：2023-02-09
申请号：US17964141
申请日：2022-10-12
Applicant: GOOGLE LLC
Inventor： Asaf Aharoni , Arun Narayanan , Nir Shabat , Parisa Haghani , Galen Tsai Chuang , Yaniv Leviathan , Neeraj Gaur , Pedro J. Moreno Mengibar , Rohit Prakash Prabhavalkar , Zhongdi Qu , Austin Severn Waters , Tomer Amiaz , Michiel A.U. Bacchiani
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an automated calling system are disclosed. In one aspect, a method includes the actions of receiving audio data of an utterance spoken by a user who is having a telephone conversation with a bot. The actions further include determining a context of the telephone conversation. The actions further include determining a user intent of a first previous portion of the telephone conversation spoken by the user and a bot intent of a second previous portion of the telephone conversation outputted by a speech synthesizer of the bot. The actions further include, based on the audio data of the utterance, the context of the telephone conversation, the user intent, and the bot intent, generating synthesized speech of a reply by the bot to the utterance. The actions further include, providing, for output, the synthesized speech.
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公开(公告)号：US11495233B2
公开(公告)日：2022-11-08
申请号：US17505913
申请日：2021-10-20
Applicant: GOOGLE LLC
Inventor： Asaf Aharoni , Arun Narayanan , Nir Shabat , Parisa Haghani , Galen Tsai Chuang , Yaniv Leviathan , Neeraj Gaur , Pedro J. Moreno Mengibar , Rohit Prakash Prabhavalkar , Zhongdi Qu , Austin Severn Waters , Tomer Amiaz , Michiel A.U. Bacchiani
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an automated calling system are disclosed. In one aspect, a method includes the actions of receiving audio data of an utterance spoken by a user who is having a telephone conversation with a bot. The actions further include determining a context of the telephone conversation. The actions further include determining a user intent of a first previous portion of the telephone conversation spoken by the user and a bot intent of a second previous portion of the telephone conversation outputted by a speech synthesizer of the bot. The actions further include, based on the audio data of the utterance, the context of the telephone conversation, the user intent, and the bot intent, generating synthesized speech of a reply by the bot to the utterance. The actions further include, providing, for output, the synthesized speech.
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公开(公告)号：US20220199084A1
公开(公告)日：2022-06-23
申请号：US17654195
申请日：2022-03-09
Applicant: Google LLC
Inventor： Wei Li , Rohit Prakash Prabhavalkar , Kanury Kanishka Rao , Yanzhang He , Ian C. McGraw , Anton Bakhtin
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting utterances of a key phrase in an audio signal. One of the methods includes receiving, by a key phrase spotting system, an audio signal encoding one or more utterances; while continuing to receive the audio signal, generating, by the key phrase spotting system, an attention output using an attention mechanism that is configured to compute the attention output based on a series of encodings generated by an encoder comprising one or more neural network layers, generating, by the key phrase spotting system and using attention output, output that indicates whether the audio signal likely encodes the key phrase; and providing, by the key phrase spotting system, the output that indicates whether the audio signal likely encodes the key phrase.
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公开(公告)号：US20220101836A1
公开(公告)日：2022-03-31
申请号：US17643423
申请日：2021-12-09
Applicant: Google LLC
Inventor： Rohit Prakash Prabhavalkar , Golan Pundak , Tara N. Sainath , Antoine Jean Bruguier
IPC: G10L15/187 , G06N20/10 , G10L19/04
Abstract: A method of biasing speech recognition includes receiving audio data encoding an utterance and obtaining a set of one or more biasing phrases corresponding to a context of the utterance. Each biasing phrase in the set of one or more biasing phrases includes one or more words. The method also includes processing, using a speech recognition model, acoustic features derived from the audio data and grapheme and phoneme data derived from the set of one or more biasing phrases to generate an output of the speech recognition model. The method also includes determining a transcription for the utterance based on the output of the speech recognition model.
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50.发明申请公开(公告)号：US20200349923A1
公开(公告)日：2020-11-05
申请号：US16861190
申请日：2020-04-28
Applicant: Google LLC
Inventor： Ke Hu , Antoine Jean Bruguier , Tara N. Sainath , Rohit Prakash Prabhavalkar , Golan Pundak
IPC: G10L15/06 , G10L15/187 , G10L15/193 , G10L15/32 , G10L15/28 , G10L25/30 , G10L15/02
Abstract: A method includes receiving audio data encoding an utterance spoken by a native speaker of a first language, and receiving a biasing term list including one or more terms in a second language different than the first language. The method also includes processing, using a speech recognition model, acoustic features derived from the audio data to generate speech recognition scores for both wordpieces and corresponding phoneme sequences in the first language. The method also includes rescoring the speech recognition scores for the phoneme sequences based on the one or more terms in the biasing term list, and executing, using the speech recognition scores for the wordpieces and the rescored speech recognition scores for the phoneme sequences, a decoding graph to generate a transcription for the utterance.
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