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:
Jan. 21, 2025

Filed:

Feb. 10, 2022
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Petar Aleksic, Jersey City, NJ (US);

Pedro Jose Moreno Mengibar, Jersey City, NJ (US);

Assignee:

Google LLC, Mountain View, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/22 (2006.01); G06F 40/295 (2020.01); G06F 40/30 (2020.01); G10L 15/26 (2006.01); G10L 15/065 (2013.01); G10L 15/183 (2013.01); G10L 15/197 (2013.01);
U.S. Cl.
CPC ...
G10L 15/22 (2013.01); G06F 40/295 (2020.01); G06F 40/30 (2020.01); G10L 15/26 (2013.01); G10L 15/065 (2013.01); G10L 15/183 (2013.01); G10L 15/197 (2013.01);
Abstract

Systems, methods, devices, and other techniques are described herein for determining dialog states that correspond to voice inputs and for biasing a language model based on the determined dialog states. In some implementations, a method includes receiving, at a computing system, audio data that indicates a voice input and determining a particular dialog state, from among a plurality of dialog states, which corresponds to the voice input. A set of n-grams can be identified that are associated with the particular dialog state that corresponds to the voice input. In response to identifying the set of n-grams that are associated with the particular dialog state that corresponds to the voice input, a language model can be biased by adjusting probability scores that the language model indicates for n-grams in the set of n-grams. The voice input can be transcribed using the adjusted language model.


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