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
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