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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.

Patent No.:

US 9627532 B1

PDFFull Text
Date of Patent:
Apr. 18, 2017

Filed:

Jun. 18, 2014

Methods and apparatus for training an artificial neural network for use in speech recognition

Applicant:

Nuance Communications, Inc., Burlington, MA (US);

Inventors:

Roberto Gemello, Alpignano, IT;

Franco Mana, Turin, IT;

Dario Albesano, Venaria Reale, IT;

Assignee:

Nuance Communications, Inc., Burlington, MA (US);

Attorney:

Wolfeld, Greenfield & Sacks, P.C.

Primary Examiner:

Michael B Holmes

Int. Cl.
CPC ...
G06E 1/00 (2006.01); G06E 3/00 (2006.01); G06F 15/18 (2006.01); G06G 7/00 (2006.01); H01L 29/78 (2006.01); G06N 3/04 (2006.01); G10L 15/16 (2006.01); H01L 27/12 (2006.01); H01L 29/06 (2006.01); H01L 29/08 (2006.01); H01L 29/10 (2006.01); H01L 29/16 (2006.01); H01L 29/161 (2006.01); H01L 29/165 (2006.01);
U.S. Cl.
CPC ...
H01L 29/7848 (2013.01); G06N 3/04 (2013.01); G10L 15/16 (2013.01); H01L 27/1211 (2013.01); H01L 29/0649 (2013.01); H01L 29/0847 (2013.01); H01L 29/1037 (2013.01); H01L 29/161 (2013.01); H01L 29/165 (2013.01); H01L 29/1608 (2013.01); H01L 29/785 (2013.01);
Abstract

Methods and apparatus for training a multi-layer artificial neural network for use in speech recognition. The method comprises determining for a first speech pattern of the plurality of speech patterns, using a first processing pipeline, network activations for a plurality of nodes of the artificial neural network in response to providing the first speech pattern as input to the artificial neural network, determining based, at least in part, on the network activations and a selection criterion, whether the artificial neural network should be trained on the first speech pattern, and updating, using a second processing pipeline, network weights between nodes of the artificial neural network based, at least in part, on the network activations when it is determined that the artificial neural network should be trained on the first speech pattern.

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