Speaker Recognition via Similar Centroids Balanced FKVQ

Author

Li Shaomei ; Guo Yunfei ; Liu Lixiong

Author_Institution

Nat. Digital Switching Syst. Res. Center, Zhengzhou, China

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

To solve the false acceptance problem in speaker recognition, definition of similar centroids among all reference speakers´ codebooks and similarity between each two speakers are given. A triple is introduced to mark each centroid with the description of similar centroids. And such triple is used to modify the target function in the fuzzy kernel vector quantization speaker recognition, in which the distortion between a test speech feature vector and a centroid is balanced by the centroid´s all similar centroids. The proposed algorithm can weaken similar centroids´ effect in recognition, and decrease false acceptance rate. Similar centroids balanced algorithm showed excellent effect in speaker recognition, and especially in the case of reference speakers with high similarity.

Keywords

fuzzy set theory; speaker recognition; vector quantisation; centroids balanced FKVQ; false acceptance rate; fuzzy kernel vector quantization; speaker recognition; Clustering algorithms; Embedded computing; Fuzzy control; Kernel; Speaker recognition; Speech; Switching systems; Testing; Training data; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4507-3

Electronic_ISBN

978-1-4244-4507-3

Type

conf

DOI

10.1109/CISE.2009.5362688

Filename

5362688