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Comparison of Two Speaker Recognition Systems

Publication Type : Journal Article

Publisher : International Journal of Engineering and Advanced Technology (IJEAT)

Campus : Coimbatore

School : School of Engineering

Department : Electronics and Communication

Year : 2014

Abstract : This paper presents a comparison between two speaker recognition systems. One system uses 30 Shannon entropy values extracted from a four level wavelet packet decomposition method in addition to the first three formant frequencies as features and a cascaded feed forward back propagation neural network is used as classifier. The second system uses Mel frequency cepstral coefficients (MFCC) as features and a support vector machine (SVM) as classifier. Results suggest that wavelet based system has better performance than the classic MFCCs with an efficiency of 89.56%.

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