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:
Jun. 13, 2023

Filed:

Feb. 28, 2020
Applicant:

Nippon Telegraph and Telephone Corporation, Tokyo, JP;

Inventors:

Tomohiro Nakatani, Tokyo, JP;

Marc Delcroix, Tokyo, JP;

Keisuke Kinoshita, Tokyo, JP;

Shoko Araki, Tokyo, JP;

Yuki Kubo, Tokyo, JP;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 21/0232 (2013.01); G10K 11/175 (2006.01); G10L 21/028 (2013.01);
U.S. Cl.
CPC ...
G10L 21/0232 (2013.01); G10K 11/1752 (2020.05); G10L 21/028 (2013.01);
Abstract

A time-variant noise spatial covariance matrix is estimated effectively. Using time-frequency-divided observation signals based on observation signals acquired by collecting acoustic signals emitted from one or a plurality of sound sources and mask information expressing the occupancy probability of a component of each of the time-frequency-divided observation signals that corresponds to each noise source, a time-independent first noise spatial covariance matrix corresponding to the time-frequency-divided observation signals and the mask information belonging to a long time interval is acquired for each noise source. Further, using the mask information of each of a plurality of different short time intervals, a mixture weight corresponding to each noise source in each short time interval is acquired. Furthermore, a time-variant third noise spatial covariance matrix is acquired, the third noise spatial covariance matrix being based on a time-variant second noise spatial covariance matrix, which corresponds to the time-frequency-divided observation signals and the mask information belonging to each short time interval and relates to noise formed by adding together all of the noise sources, and a weighted sum of the first noise spatial covariance matrices with the mixture weights of the respective short time intervals.


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