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. 30, 2023

Filed:

May. 13, 2021
Applicant:

Neosapience, Inc., Seoul, KR;

Inventors:

Suwon Shon, Seoul, KR;

Younggun Lee, Seoul, KR;

Taesu Kim, Suwon-si, KR;

Assignee:

NEOSAPIENCE, INC., Seoul, KR;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/10 (2006.01); G06F 16/901 (2019.01); G06F 16/683 (2019.01); G06N 3/04 (2023.01); G10L 15/02 (2006.01); G10L 25/03 (2013.01);
U.S. Cl.
CPC ...
G10L 15/10 (2013.01); G06F 16/683 (2019.01); G06F 16/9014 (2019.01); G06N 3/04 (2013.01); G10L 15/02 (2013.01); G10L 25/03 (2013.01);
Abstract

A method for searching content having same voice as a voice of a target speaker from among a plurality of contents includes extracting a feature vector corresponding to the voice of the target speaker, selecting any subset of speakers from a training dataset repeatedly by a predetermined number of times, generating linear discriminant analysis (LDA) transformation matrices using each of the selected any subsets of speakers repeatedly by a predetermined number of times, projecting the extracted speaker feature vector to the selected corresponding subsets of speakers using each of the generated LDA transformation matrices, assigning a value corresponding to nearby speaker class among corresponding subsets of speakers, to each of projection regions of the extracted speaker feature vector, generating a hash value corresponding to the extracted feature vector based on the assigned values, and searching content having a similar hash value to the generated hash value among the contents.


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