The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 01, 2024

Filed:

Sep. 20, 2021
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Rohit Prakash Prabhavalkar, Mountain View, CA (US);

Zhifeng Chen, Sunnyvale, CA (US);

Bo Li, Fremont, CA (US);

Chung-cheng Chiu, Sunnyvale, CA (US);

Kanury Kanishka Rao, Santa Clara, CA (US);

Yonghui Wu, Fremont, CA (US);

Ron J. Weiss, New York, NY (US);

Navdeep Jaitly, Mountain View, CA (US);

Michiel A. u. Bacchiani, Summit, NJ (US);

Tara N. Sainath, Jersey City, NJ (US);

Jan Kazimierz Chorowski, Poland, PL;

Anjuli Patricia Kannan, Berkeley, CA (US);

Ekaterina Gonina, Sunnyvale, CA (US);

Patrick An Phu Nguyen, Palo Alto, CA (US);

Assignee:

Google LLC, Mountain View, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/00 (2013.01); G06N 3/08 (2023.01); G10L 15/02 (2006.01); G10L 15/06 (2013.01); G10L 15/16 (2006.01); G10L 15/22 (2006.01); G10L 25/30 (2013.01); G10L 15/26 (2006.01);
U.S. Cl.
CPC ...
G10L 15/16 (2013.01); G06N 3/08 (2013.01); G10L 15/02 (2013.01); G10L 15/063 (2013.01); G10L 15/22 (2013.01); G10L 25/30 (2013.01); G10L 2015/025 (2013.01); G10L 15/26 (2013.01);
Abstract

A method for performing speech recognition using sequence-to-sequence models includes receiving audio data for an utterance and providing features indicative of acoustic characteristics of the utterance as input to an encoder. The method also includes processing an output of the encoder using an attender to generate a context vector, generating speech recognition scores using the context vector and a decoder trained using a training process, and generating a transcription for the utterance using word elements selected based on the speech recognition scores. The transcription is provided as an output of the ASR system.


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