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. 02, 2018

Filed:

Aug. 01, 2016
Applicant:

Apple Inc., Cupertino, CA (US);

Inventors:

Lalin S. Theverapperuma, Cupertino, CA (US);

Vasu Iyengar, Pleasanton, CA (US);

Sarmad Aziz Malik, Cupertino, CA (US);

Raghavendra Prabhu, Culver City, CA (US);

Assignee:

Apple Inc., Cupertino, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 25/30 (2013.01); G10L 21/0232 (2013.01); G10L 25/72 (2013.01); G10L 25/84 (2013.01); G10L 21/028 (2013.01);
U.S. Cl.
CPC ...
G10L 25/30 (2013.01); G10L 21/028 (2013.01); G10L 21/0232 (2013.01); G10L 25/72 (2013.01); G10L 25/84 (2013.01);
Abstract

Method of speech enhancement using Neural Network-based combined signal starts with training neural network offline which includes: (i) exciting at least one accelerometer and at least one microphone using training accelerometer signal and training acoustic signal, respectively. The training accelerometer signal and the training acoustic signal are correlated during clean speech segments. Training neural network offline further includes (ii) selecting speech included in the training accelerometer signal and in the training acoustic signal, and (iii) spatially localizing the speech by setting a weight parameter in the neural network based on the selected speech included in the training accelerometer signal and in the training acoustic signal. The neural network that is trained offline is then used to generate a speech reference signal based on an accelerometer signal from the at least one accelerometer and an acoustic signal received from the at least one microphone. Other embodiments are described.


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