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:
Jul. 12, 2016

Filed:

Jan. 26, 2015
Applicants:

Sogang University Research Foundation, Seoul, KR;

Kangwon National University University-industry Cooperation Foundation, Chuncheon-si, KR;

Inventors:

Jung Yun Seo, Seoul, KR;

Sang Woo Kang, Seoul, KR;

Myoung-Wan Koo, Seoul, KR;

Hark Soo Kim, Seoul, KR;

Hyeok Ju Ahn, Wonju-si, KR;

Yeong Kil Song, Chuncheon-si, KR;

Maeng Sik Choi, Samcheok-si, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/06 (2013.01);
U.S. Cl.
CPC ...
G10L 15/063 (2013.01); G10L 2015/0635 (2013.01);
Abstract

Provided is a speech recognition method using machine learning, including: receiving a speech signal as an input, performing speech recognition to generate speech recognition result information including multiple candidate sentences and ranks of the respective candidate sentences; processing the multiple candidate sentences included in the speech recognition result information according to a machine learning model which is learned in advance and changing the ranks of the multiple candidate sentences to re-rank the multiple candidate sentences; and selecting the highest-rank candidate sentence among the re-ranked multiple candidate sentences as a speech recognition result. Particularly, the machine learning model is generated by: receiving the speech signal and a correct answer sentence as inputs; generating the speech recognition result information and a correct answer set; generating learning data by using the correct answer set; and performing the machine learning of changing the ranks of the candidate sentences.


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