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. 04, 2016

Filed:

Apr. 15, 2013
Applicant:

Google Inc., Mountain View, CA (US);

Inventors:

Vincent Olivier Vanhoucke, San Francisco, CA (US);

Jeffrey Adgate Dean, Palo Alto, CA (US);

Georg Heigold, Mountain View, CA (US);

Marc'aurelio Ranzato, Mountain View, CA (US);

Matthieu Devin, Los Altos Hills, CA (US);

Patrick An Phu Nguyen, Palo Alto, CA (US);

Andrew William Senior, New York, NY (US);

Assignee:

Google Inc., Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/00 (2013.01); G10L 15/16 (2006.01); G06F 17/28 (2006.01); G10L 15/26 (2006.01);
U.S. Cl.
CPC ...
G10L 15/16 (2013.01);
Abstract

Methods and systems for processing multilingual DNN acoustic models are described. An example method may include receiving training data that includes a respective training data set for each of two or more or languages. A multilingual deep neural network (DNN) acoustic model may be processed based on the training data. The multilingual DNN acoustic model may include a feedforward neural network having multiple layers of one or more nodes. Each node of a given layer may connect with a respective weight to each node of a subsequent layer, and the multiple layers of one or more nodes may include one or more shared hidden layers of nodes and a language-specific output layer of nodes corresponding to each of the two or more languages. Additionally, weights associated with the multiple layers of one or more nodes of the processed multilingual DNN acoustic model may be stored in a database.


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