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. 17, 2026

Filed:

Mar. 07, 2024
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Ke Hu, Stony Brook, NY (US);

Bo Li, Santa Clara, CA (US);

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

Yu Zhang, Mountain View, CA (US);

Francoise Beaufays, Mountain View, CA (US);

Assignee:

Google LLC, Mountain View, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/197 (2013.01); G10L 15/02 (2006.01); G10L 15/06 (2013.01);
U.S. Cl.
CPC ...
G10L 15/197 (2013.01); G10L 15/02 (2013.01); G10L 15/063 (2013.01);
Abstract

A method of a multilingual ASR model includes receiving a sequence of acoustic frames characterizing an utterance of speech. At a plurality of output steps, the method further includes generating a first higher order feature representation for an acoustic frame by a first encoder that includes a first plurality of multi-head attention layers; generating a second higher order feature representation for a corresponding first higher order feature representation by a second encoder that includes a second plurality of multi-head attention layers; and generating, by a first decoder, a first probability distribution over possible speech recognition hypotheses based on the second higher order feature representation and a sequence of N previous non-blank symbols. A gating layer of each respective MoE layer configured to dynamically route an output from a previous multi-head attention layer at each of the plurality of output steps to a respective pair of feed-forward expert networks.


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