Performance analysis of speaker features extracted from high-order fractional domains

Author

Jinfang, Wang ; Jinbao, Wang

Author_Institution

Dept. of Inf. Eng., Jilin Univ., Changchun

fYear

0

fDate

0-0 0

Lastpage

4

Abstract

An evaluation of the feature set of the vector difference (VD) based on fractional cosine and sine transform focusing on the high-order fractional domains for text-independent speaker recognition is elucidated in this paper. The experiments have been done following the principles varying the number of the vector dimension and the power of the output parameters of fractional cosine and sine transform separately. The recognition results show that when the order of primary fractional domain is fixed to be 1 and the one of secondary fractional domain is 0.98, the correct recognition rate of the VD feature matches the one of the previous MFCC feature

Keywords

feature extraction; speaker recognition; speech processing; transforms; fractional cosine transform; high-order fractional domains; sine transform; speaker features extracted; text-independent speaker recognition; vector difference; Cepstrum; Data mining; Feature extraction; Linear predictive coding; Mel frequency cepstral coefficient; Performance analysis; Performance evaluation; Speaker recognition; Speech processing; Time frequency analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Control Applications, 2005. ICIECA 2005. International Conference on

Conference_Location

Quito

Print_ISBN

0-7803-9419-4

Type

conf

DOI

10.1109/ICIECA.2005.1644383

Filename

1644383