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:
Aug. 06, 2019

Filed:

Feb. 02, 2017
Applicant:

Kabushiki Kaisha Toshiba, Minato-ku, JP;

Inventors:

Javier Latorre-Martinez, Cambridge, GB;

Vincent Ping Leung Wan, Cambridge, GB;

Kayoko Yanagisawa, Cambridge, GB;

Assignee:

Kabushiki Kaisha Toshiba, Minato-ku, JP;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 13/08 (2013.01); G10L 15/065 (2013.01); G10L 15/07 (2013.01); G10L 15/16 (2006.01); G10L 15/20 (2006.01); G10L 13/00 (2006.01); G10L 13/047 (2013.01); G10L 15/26 (2006.01);
U.S. Cl.
CPC ...
G10L 13/08 (2013.01); G10L 13/00 (2013.01); G10L 15/065 (2013.01); G10L 15/07 (2013.01); G10L 15/075 (2013.01); G10L 15/16 (2013.01); G10L 15/20 (2013.01); G10L 13/047 (2013.01); G10L 15/265 (2013.01);
Abstract

An acoustic model is adapted, relating acoustic units to speech vectors. The acoustic model comprises a set of acoustic model parameters related to a given speech factor. The acoustic model parameters enable the acoustic model to output speech vectors with different values of the speech factor. The method comprises inputting a sample of speech which is corrupted by noise; determining values of the set of acoustic model parameters which enable the acoustic model to output speech with said first value of the speech factor; and employing said determined values of the set of speech factor parameters in said acoustic model. The acoustic model parameters are obtained by obtaining corrupted speech factor parameters using the sample of speech, and mapping the corrupted speech factor parameters to clean acoustic model parameters using noise characterization paramaters characterizing the noise.


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