公开(公告)号：US11238242B2

公开(公告)日：2022-02-01

申请号：US16360752

申请日：2019-03-21

Applicant: Google LLC

Inventor： Wan Fen Nicole Quah ,  Bryan Horling ,  Maryam Garrett ,  Brian Roark ,  Richard Sproat

IPC: G06F40/00 ,  G06F40/40 ,  G06F16/31 ,  H04L12/58 ,  G06F40/30 ,  G06F40/56 ,  G06F40/151 ,  G06F40/268 ,  G06F40/284

Abstract: Some implementations are directed to translating chatspeak to a normalized form, where the chatspeak is included in natural language input formulated by a user via a user interface input device of a computing device—such as input provided by the user to an automated assistant. The normalized form of the chatspeak may be utilized by the automated assistant in determining reply content that is responsive to the natural language input, and that reply content may be presented to the user via one or more user interface output devices of the computing device of the user. Some implementations are additionally and/or alternatively directed to providing, for presentation to a user, natural language output that includes chatspeak in lieu of a normalized form of the chatspeak, based at least in part on a “chatspeak measure” that is determined based on past usage of chatspeak by the user and/or by additional users.

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

IPC: G10L15/00 ,  G06F40/58 ,  G06N3/04 ,  G10L15/06 ,  G10L15/16 ,  G10L15/26 ,  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.

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

IPC: G10L15/00 ,  G10L15/16 ,  G10L15/26 ,  G06F40/58 ,  G10L15/06

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.

公开(公告)号：US20190220519A1

公开(公告)日：2019-07-18

申请号：US16360752

申请日：2019-03-21

Applicant: Google LLC

Inventor： Wan Fen Nicole Quah ,  Bryan Horling ,  Maryam Garrett ,  Brian Roark ,  Richard Sproat

IPC: G06F17/28 ,  G06F16/31 ,  H04L12/58 ,  G06F17/27 ,  G06F17/22

CPC classification number: G06F17/28 ,  G06F16/313 ,  G06F17/2264 ,  G06F17/2755 ,  G06F17/277 ,  G06F17/2785 ,  G06F17/2881 ,  H04L51/04 ,  H04L51/046 ,  H04L51/16

Abstract: Some implementations are directed to translating chatspeak to a normalized form, where the chatspeak is included in natural language input formulated by a user via a user interface input device of a computing device—such as input provided by the user to an automated assistant. The normalized form of the chatspeak may be utilized by the automated assistant in determining reply content that is responsive to the natural language input, and that reply content may be presented to the user via one or more user interface output devices of the computing device of the user. Some implementations are additionally and/or alternatively directed to providing, for presentation to a user, natural language output that includes chatspeak in lieu of a normalized form of the chatspeak, based at least in part on a “chatspeak measure” that is determined based on past usage of chatspeak by the user and/or by additional users.