Speech Recognition and Verification using MFCC & VQ

Abstract

Speech recognition is very important branch in digital signal processing. Speaker Recognition software using MFCC (Mel Frequency Cepstral Co-efficient) and vector quantization has been designed, developed and tested satisfactorily for male and female voice. In this paper the ability of HPS (Harmonic Product Spectrum) algorithm and MFCC for gender and speaker recognition is explored. HPS algorithm can be used to find the pitch of the speaker which can be used to determine gender of the speaker. In this algorithm the speech signals for male and female ware recorded in .wav(dot wav) file at 8 KHz sampling rate and then modified. This modified wav file for speech signal was processed using MATLAB software for computing and plotting the autocorrelation of speech signal. The software reliably computes the pitch of male and female voice. The MFCC algorithm is used to simulate feature extraction module. Using this algorithm the cepstral co-efficient are calculated of Mel frequency scale. VQ (Vector Quantization) method will be used for reduction of amount of data to decrease computation time. In the feature matching stage Euclidean distance is applied as similarity criterion. Because of high accuracy of used algorithm the accuracy of voice command system is high. In this paper the quality and testing of speaker recognition and gender recognition system is completed and analysed.

Speech recognition is very important branch in digital signal processing. Speaker Recognition software using MFCC (Mel Frequency Cepstral Co-efficient) and vector quantization has been designed, developed and tested satisfactorily for male and female voice. In this paper the ability of HPS (Harmonic Product Spectrum) algorithm and MFCC for gender and speaker recognition is explored. HPS algorithm can be used to find the pitch of the speaker which can be used to determine gender of the speaker. In this algorithm the speech signals for male and female ware recorded in .wav(dot wav) file at 8 KHz sampling rate and then modified. This modified wav file for speech signal was processed using MATLAB software for computing and plotting the autocorrelation of speech signal. The software reliably computes the pitch of male and female voice. The MFCC algorithm is used to simulate feature extraction module. Using this algorithm the cepstral co-efficient are calculated of Mel frequency scale. VQ (Vector Quantization) method will be used for reduction of amount of data to decrease computation time. In the feature matching stage Euclidean distance is applied as similarity criterion. Because of high accuracy of used algorithm the accuracy of voice command system is high. In this paper the quality and testing of speaker recognition and gender recognition system is completed and analysed.