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, 2019

Filed:

Nov. 03, 2017
Applicant:

Apple Inc., Cupertino, CA (US);

Inventors:

Matthias Paulik, San Jose, CA (US);

Gunnar Evermann, Boston, MA (US);

Laurence S. Gillick, Newton, MA (US);

Assignee:

Apple Inc., Cupertino, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/27 (2006.01); G10L 15/06 (2013.01); G10L 15/02 (2006.01); G10L 25/33 (2013.01); G10L 15/197 (2013.01); G06F 16/9535 (2019.01); G10L 15/18 (2013.01); G10L 15/183 (2013.01);
U.S. Cl.
CPC ...
G10L 15/063 (2013.01); G06F 16/9535 (2019.01); G10L 15/02 (2013.01); G10L 15/197 (2013.01); G10L 25/33 (2013.01); G10L 15/183 (2013.01); G10L 15/1815 (2013.01);
Abstract

Systems and processes are disclosed for discovering trending terms in automatic speech recognition. Candidate terms (e.g., words, phrases, etc.) not yet found in a speech recognizer vocabulary or having low language model probability can be identified based on trending usage in a variety of electronic data sources (e.g., social network feeds, news sources, search queries, etc.). When candidate terms are identified, archives of live or recent speech traffic can be searched to determine whether users are uttering the candidate terms in dictation or speech requests. Such searching can be done using open vocabulary spoken term detection to find phonetic matches in the audio archives. As the candidate terms are found in the speech traffic, notifications can be generated that identify the candidate terms, provide relevant usage statistics, identify the context in which the terms are used, and the like.


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