Research of speaker recognition based on the weighted fisher ratio of MFCC

Feature extraction and pattern recognition are two important technologies of speaker recognition system. We introduced the existing speaker recognition technology in this paper, proposed and implemented a speaker recognition algorithm based on the weighted fisher ratio of MFCC. Compared with the traditional feature selection methods, the characteristic vector obtained via this algorithm has the greatest degree of differentiation in the same dimension. To evaluate performance of this algorithm, we built a small speaker recognition system based on the MATLAB. According to the test results, the speaker recognition algorithm we proposed in this paper, can significantly increase the accuracy rate of training and recognition, and reduce the data required by calculation, in the case of keeping a higher recognition rate.