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:
Sep. 29, 2020

Filed:

Sep. 28, 2018
Applicant:

Intel Corporation, Santa Clara, CA (US);

Inventors:

Kuba Lopatka, Gdansk, PL;

Mateusz Kotarski, Sopot, PL;

Tobias Bocklet, Kronach, DE;

Marek Zabkiewicz, Gdynia, PL;

Assignee:

Intel Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/16 (2006.01); G10L 15/22 (2006.01); G10L 15/02 (2006.01); G06N 3/04 (2006.01); G06F 17/14 (2006.01); G06K 9/00 (2006.01); G06K 9/62 (2006.01); G10L 25/51 (2013.01); G06N 3/08 (2006.01); G06F 9/54 (2006.01); G06K 9/46 (2006.01);
U.S. Cl.
CPC ...
G10L 15/16 (2013.01); G06F 9/542 (2013.01); G06F 17/147 (2013.01); G06K 9/00536 (2013.01); G06K 9/4628 (2013.01); G06K 9/627 (2013.01); G06N 3/04 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G10L 15/02 (2013.01); G10L 15/22 (2013.01); G10L 25/51 (2013.01);
Abstract

Techniques are provided for efficient acoustic event detection with reduced resource consumption. A methodology implementing the techniques according to an embodiment includes calculating frames of power spectra based on segments of received acoustic signals. The method further includes two processes, one for detecting impulsive acoustic events and another for detecting continuous acoustic events. The first process includes generating impulsive acoustic event features associated with first and second power spectrum frames, applying a neural network classifier to the impulsive acoustic event features to generate event scores, and detecting an impulsive acoustic event based on those event scores. The second process includes generating reduced-dimension continuous acoustic event features associated with the first and second power spectrum frames, applying a neural network classifier to the reduced-dimension continuous acoustic event features to generate a second set of event scores, and detecting a continuous acoustic event based on the second set of event scores.


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