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Patent Agency Ranking
公开(公告)号：US11468244B2
公开(公告)日：2022-10-11
申请号：US16834342
申请日：2020-03-30
Applicant: Google LLC
Inventor： Anjuli Patricia Kannan , Tara N. Sainath , Yonghui Wu , Ankur Bapna , Arindrima Datta
Abstract: A method of transcribing speech using a multilingual end-to-end (E2E) speech recognition model includes receiving audio data for an utterance spoken in a particular native language, obtaining a language vector identifying the particular language, and processing, using the multilingual E2E speech recognition model, the language vector and acoustic features derived from the audio data to generate a transcription for the utterance. The multilingual E2E speech recognition model includes a plurality of language-specific adaptor modules that include one or more adaptor modules specific to the particular native language and one or more other adaptor modules specific to at least one other native language different than the particular native language. The method also includes providing the transcription for output.
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公开(公告)号：US11615779B2
公开(公告)日：2023-03-28
申请号：US17152760
申请日：2021-01-19
Applicant: Google LLC
Inventor： Arindrima Datta , Bhuvana Ramabhadran , Jesse Emond , Brian Roark
Abstract: A method includes obtaining a plurality of training data sets each associated with a respective native language and includes a plurality of respective training data samples. For each respective training data sample of each training data set in the respective native language, the method includes transliterating the corresponding transcription in the respective native script into corresponding transliterated text representing the respective native language of the corresponding audio in a target script and associating the corresponding transliterated text in the target script with the corresponding audio in the respective native language to generate a respective normalized training data sample. The method also includes training, using the normalized training data samples, a multilingual end-to-end speech recognition model to predict speech recognition results in the target script for corresponding speech utterances spoken in any of the different native languages associated with the plurality of training data sets.
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公开(公告)号：US20210233510A1
公开(公告)日：2021-07-29
申请号：US17152760
申请日：2021-01-19
Applicant: Google LLC
Inventor： Arindrima Datta , Bhuvana Ramabhadran , Jesse Emond , Brian Roak
Abstract: A method includes obtaining a plurality of training data sets each associated with a respective native language and includes a plurality of respective training data samples. For each respective training data sample of each training data set in the respective native language, the method includes transliterating the corresponding transcription in the respective native script into corresponding transliterated text representing the respective native language of the corresponding audio in a target script and associating the corresponding transliterated text in the target script with the corresponding audio in the respective native language to generate a respective normalized training data sample. The method also includes training, using the normalized training data samples, a multilingual end-to-end speech recognition model to predict speech recognition results in the target script for corresponding speech utterances spoken in any of the different native languages associated with the plurality of training data sets.
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公开(公告)号：US20230223009A1
公开(公告)日：2023-07-13
申请号：US18187330
申请日：2023-03-21
Applicant: Google LLC
Inventor： Arindrima Datta , Bhuvana Ramabhadran , Jesse Emond , Brian Roark
CPC classification number: G10L15/005 , G10L15/16 , G10L15/26 , G06F40/58 , G10L15/063 , G06N3/049
Abstract: A method includes obtaining a plurality of training data sets each associated with a respective native language and includes a plurality of respective training data samples. For each respective training data sample of each training data set in the respective native language, the method includes transliterating the corresponding transcription in the respective native script into corresponding transliterated text representing the respective native language of the corresponding audio in a target script and associating the corresponding transliterated text in the target script with the corresponding audio in the respective native language to generate a respective normalized training data sample. The method also includes training, using the normalized training data samples, a multilingual end-to-end speech recognition model to predict speech recognition results in the target script for corresponding speech utterances spoken in any of the different native languages associated with the plurality of training data sets.
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公开(公告)号：US20200380215A1
公开(公告)日：2020-12-03
申请号：US16834342
申请日：2020-03-30
Applicant: Google LLC
Inventor： Anjuli Patricia Kannan , Tara N. Sainath , Yonghui Wu , Ankur Bapna , Arindrima Datta
Abstract: A method of transcribing speech using a multilingual end-to-end (E2E) speech recognition model includes receiving audio data for an utterance spoken in a particular native language, obtaining a language vector identifying the particular language, and processing, using the multilingual E2E speech recognition model, the language vector and acoustic features derived from the audio data to generate a transcription for the utterance. The multilingual E2E speech recognition model includes a plurality of language-specific adaptor modules that include one or more adaptor modules specific to the particular native language and one or more other adaptor modules specific to at least one other native language different than the particular native language. The method also includes providing the transcription for output.
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