Speaker Identification and Verification using Vector Quantization and Mel Frequency Cepstral Coefficients

In the study of speaker recognition, Mel Frequency Cepstral Coefficient (MFCC) method is the best and most popular which is used to feature extraction. Further vector quantization technique is used to minimize the amount of data to be handled in recent years. In the present paper, the Speaker Recognition using Mel Frequency Cepstral coefficients and vector Quantization for the letter “Zha” (in Tamil language) is obtained. The experimental results are analyzed with the help of MATLAB in different situations and it is proved that the results are efficient in the noisy environment.