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. 07, 2020

Filed:

Jan. 18, 2019
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Izhak Shafran, Menlo Park, CA (US);

Thomas E. Bagby, San Francisco, CA (US);

Russell John Wyatt Skerry-Ryan, Mountain View, CA (US);

Assignee:

Google LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/16 (2006.01); G10L 19/02 (2013.01); G10L 15/02 (2006.01); G10H 1/00 (2006.01); G06N 3/02 (2006.01); G10L 17/18 (2013.01); G10L 25/30 (2013.01);
U.S. Cl.
CPC ...
G10L 15/16 (2013.01); G06N 3/02 (2013.01); G10H 1/00 (2013.01); G10L 15/02 (2013.01); G10L 19/0212 (2013.01); G10H 2210/036 (2013.01); G10H 2210/046 (2013.01); G10H 2250/235 (2013.01); G10H 2250/311 (2013.01); G10L 17/18 (2013.01); G10L 25/30 (2013.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech recognition using complex evolution recurrent neural networks. In some implementations, audio data indicating acoustic characteristics of an utterance is received. A first vector sequence comprising audio features determined from the audio data is generated. A second vector sequence is generated, as output of a first recurrent neural network in response to receiving the first vector sequence as input, where the first recurrent neural network has a transition matrix that implements a cascade of linear operators comprising (i) first linear operators that are complex-valued and unitary, and (ii) one or more second linear operators that are non-unitary. An output vector sequence of a second recurrent neural network is generated. A transcription for the utterance is generated based on the output vector sequence generated by the second recurrent neural network. The transcription for the utterance is provided.


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