DocumentCode :
2095182
Title :
A New Algorithm for Auditory Feature Extraction
Author :
Xu, He ; Lin, Lin ; Sun, Xiaoying ; Jin, Huanmei
Author_Institution :
Coll. Commun. Eng., Jilin Univ., Changchun, China
fYear :
2012
fDate :
11-13 May 2012
Firstpage :
229
Lastpage :
232
Abstract :
The human auditory system possesses remarkable capabilities to analyze and identify signals. An auditory feature can improve the performance of speaker recognition system. In this paper, it used gammatone filter to model auditory system, and extracted a traditional auditory feature based on logarithmic energy. On the purpose to reduce the dimension of the traditional auditory feature which was always a high dimensional feature, we took use of discrete cosine transform (DCT). Therefore, it was feasible to apply auditory model extracted in a new way to speech feature extraction. The experiments showed that the GFCC feature, which was extracted in the new method, performed better than the traditional MFCC feature in the speaker recognition system based on GMM model.
Keywords :
discrete cosine transforms; feature extraction; filtering theory; hearing; speaker recognition; GFCC feature; GMM model; auditory feature extraction; discrete cosine transform; gammatone filter; human auditory system; logarithmic energy; speaker recognition system; speech feature extraction; Auditory system; Band pass filters; Discrete cosine transforms; Ear; Feature extraction; Mel frequency cepstral coefficient; Speaker recognition; Auditory system; DCT; GFCC; Gammatone; speaker recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Systems and Network Technologies (CSNT), 2012 International Conference on
Conference_Location :
Rajkot
Print_ISBN :
978-1-4673-1538-8
Type :
conf
DOI :
10.1109/CSNT.2012.57
Filename :
6200631
Link To Document :
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