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:
Jun. 03, 2025

Filed:

Jan. 20, 2022
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Matthew Sharifi, Kilchberg, CH;

Victor Carbune, Zurich, CH;

Assignee:

GOOGLE LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 13/00 (2006.01); G06Q 10/087 (2023.01); G06Q 30/018 (2023.01); G06Q 30/02 (2023.01); G06Q 30/0207 (2023.01); G10L 15/05 (2013.01); G10L 15/16 (2006.01); G10L 15/22 (2006.01); G10L 15/26 (2006.01); G10L 25/75 (2013.01); H04M 1/72466 (2021.01); H04M 3/493 (2006.01); H04R 27/00 (2006.01); B65G 1/127 (2006.01);
U.S. Cl.
CPC ...
G10L 15/05 (2013.01); G10L 13/00 (2013.01); G10L 15/22 (2013.01); G10L 15/26 (2013.01); B65G 1/127 (2013.01); G06Q 10/087 (2013.01); G06Q 30/0185 (2013.01); G06Q 30/02 (2013.01); G10L 2015/227 (2013.01); H04M 3/4938 (2013.01); H04R 27/00 (2013.01);
Abstract

A personalized endpointing measure can be used to determine whether a user has finished speaking a spoken utterance. Various implementations include using the personalized endpointing measure to determine whether a candidate endpoint indicates a user has finished speaking the spoken utterance or whether the user has paused and has not finished speaking the spoken utterance. Various implementations include determining the personalized endpointing measure based on a portion of a text representation of the spoken utterance immediately preceding the candidate endpoint and a user-specific measure. Additionally or alternatively, the user-specific measure can be based on the text representation immediately preceding the candidate endpoint and one or more historical interactions with the user. In various implementations, each of the historical interactions are specific to the text representation and the user, and indicate whether a previous instance of the text representation was a previous endpoint for the user.


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