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:
Mar. 30, 2021

Filed:

Jun. 30, 2017
Applicant:

Amazon Technologies, Inc., Seattle, WA (US);

Inventors:

Minhua Wu, San Jose, CA (US);

Sankaran Panchapagesan, Mountain View, CA (US);

Ming Sun, Winchester, MA (US);

Shiv Naga Prasad Vitaladevuni, Belmont, MA (US);

Bjorn Hoffmeister, Seattle, WA (US);

Ryan Paul Thomas, Redmond, WA (US);

Arindam Mandal, Redwood City, CA (US);

Assignee:

Amazon Technologies, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/22 (2006.01); G10L 15/14 (2006.01); G10L 15/02 (2006.01); G10L 15/16 (2006.01); G10L 25/30 (2013.01); G10L 15/08 (2006.01);
U.S. Cl.
CPC ...
G10L 15/22 (2013.01); G10L 15/02 (2013.01); G10L 15/142 (2013.01); G10L 15/16 (2013.01); G10L 25/30 (2013.01); G10L 2015/025 (2013.01); G10L 2015/088 (2013.01); G10L 2015/223 (2013.01);
Abstract

An approach to wakeword detection uses an explicit representation of non-wakeword speech in the form of subword (e.g., phonetic monophone) units that do not necessarily occur in the wakeword and that broadly represent general speech. These subword units are arranged in a 'background' model, which at runtime essentially competes with the wakeword model such that a wakeword is less likely to be declare as occurring when the input matches that background model well. An HMM may be used with the model to locate possible occurrences of the wakeword. Features are determined from portions of the input corresponding to subword units of the wakeword detected using the HMM. A secondary classifier is then used to process the features to yield a decision of whether the wakeword occurred.


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