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:
Jan. 28, 2025

Filed:

Jun. 19, 2020
Applicant:

Nippon Telegraph and Telephone Corporation, Tokyo, JP;

Inventors:

Tomohiro Nakatani, Tokyo, JP;

Keisuke Kinoshita, Tokyo, JP;

Marc Delcroix, Tokyo, JP;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04R 3/00 (2006.01); G06N 3/084 (2023.01); G10K 11/175 (2006.01); G10K 11/34 (2006.01); H04R 1/40 (2006.01);
U.S. Cl.
CPC ...
H04R 3/005 (2013.01); G06N 3/084 (2013.01); G10K 11/1752 (2020.05); G10K 11/34 (2013.01); H04R 1/406 (2013.01);
Abstract

Provided is a target sound extraction technique based on a steering vector generation method enabling instability in a calculation to be prevented when a neural network is trained by using an error back propagation method to reduce an estimation error of a beamformer. A target sound signal generation apparatus generates a target sound signal ycorresponding to a target sound included in an observed sound from an observed signal vector xcorresponding to the observed sound collected by using a plurality of microphones. The target sound signal generation apparatus includes a mask generation unit, a steering vector generation unit, a beamformer vector generation unit, and a target sound signal generation unit. The mask generation unit is configured as a neural network trained by using an error back propagation method. The steering vector generation unit generates a steering vector hby determining an eigenvector corresponding to a maximum eigenvalue of a predetermined matrix generated from the observed signal vector xand a mask γby using a power method.


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