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:
May. 21, 2019

Filed:

Aug. 28, 2016
Applicant:

Malaspina Labs (Barbados), Inc., Vancouver, CA;

Inventor:

Robert Alex Fuhrman, Vancouver, CA;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/02 (2006.01); G10L 15/12 (2006.01); G10L 15/16 (2006.01); G10L 25/30 (2013.01); G10L 15/06 (2013.01); G10L 15/20 (2006.01); G10L 15/197 (2013.01);
U.S. Cl.
CPC ...
G10L 15/063 (2013.01); G10L 15/02 (2013.01); G10L 15/16 (2013.01); G10L 15/197 (2013.01); G10L 15/20 (2013.01); G10L 2015/025 (2013.01); G10L 2015/0635 (2013.01);
Abstract

Various implementations disclosed herein include a phonotactic post-processor configured to rescore the N-best phoneme candidates output by a primary ensemble phoneme neural network using a priori phonotactic information. In various implementations, one of the scored set of the N-best phoneme candidates is selected as a preferred estimate for a one-phoneme output decision by the phonotactic post-processor. In some implementations, the one-phoneme output decision is an estimate of the most likely detected and recognized phoneme in a frame based on a function of posterior probabilities generated by an ensemble phoneme neural network, as well as phonotactic information and statistical performance characterizations incorporated by the phonotactic post-processor. More specifically, in various implementations, a phonotactic post-processor as described herein utilizes a priori known patterns of phonotactic structure representative of higher-level linguistic structure, instead of configuring the system to learn to recognize the higher-level linguistic structure a posteriori.


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