DocumentCode :
501741
Title :
Pitch in Speaker Recognition
Author :
Zhu Jian-wei ; Sun Shui-fa ; Liu Xiao-li ; Lei Bang-jun
Author_Institution :
Coll. of Electr. Eng. & Inf. Technol., China Three Gorges Univ., Yichang, China
Volume :
1
fYear :
2009
fDate :
12-14 Aug. 2009
Firstpage :
33
Lastpage :
36
Abstract :
In order to improve the speaker recognition accuracy, the pitch is applied to GMM-based speaker recognition (SR). The circular average magnitude difference function (CAMDF) method is used to extract the pitch. An endpoint detection method based on the pitch is proposed. The following four features are selected as the features of the SR: the mel-frequency cepstral coefficient (MFCC) based on the pitch, the pitch contour, the pitch first-order difference and the pitch changed rate. Experimental results show that the recognition rate using proposed endpoint detection method is improved 20% than that using the conventional method. The recognition rate of the proposed system using the selected four features is improved 5% than that of the speaker recognition system using the MFCC parameters only.
Keywords :
Gaussian processes; cepstral analysis; feature extraction; speaker recognition; CAMDF method; GMM-based speaker recognition; Gaussian mixture model; MFCC; circular average magnitude difference function; endpoint detection method; feature selection; mel-frequency cepstral coefficient; pitch extraction; Data mining; Educational institutions; Feature extraction; Hybrid intelligent systems; Information technology; Mel frequency cepstral coefficient; Speaker recognition; Speech recognition; Strontium; Sun; MFCC; endpoint detection; pitch; pitch contour; speaker recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-0-7695-3745-0
Type :
conf
DOI :
10.1109/HIS.2009.14
Filename :
5254359
Link To Document :
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