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%.