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:
Feb. 13, 2024

Filed:

Jan. 10, 2022
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Zhifeng Chen, Sunnyvale, CA (US);

Bo Li, Fremont, CA (US);

Eugene Weinstein, New York, NY (US);

Yonghui Wu, Fremont, CA (US);

Pedro J. Moreno Mengibar, Jersey City, NJ (US);

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

Khe Chai Sim, Cupertino, CA (US);

Tara N. Sainath, Jersey City, NJ (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); G10L 15/16 (2006.01); G10L 15/07 (2013.01); G10L 15/06 (2013.01);
U.S. Cl.
CPC ...
G10L 15/005 (2013.01); G10L 15/07 (2013.01); G10L 15/16 (2013.01); G10L 2015/0631 (2013.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. In some implementations, audio data indicating audio characteristics of an utterance is received. Input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. The speech recognition model can be one that has been trained using cluster adaptive training. Output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. A transcription of the utterance generated based on the output of the speech recognition model is provided.


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