Base on the Fusion Parameters of Cepstrum Components Used in Speaker Recognition

Voiceprint recognition technology is a new kind of biological certification technology. With the rapid development of Internet research bring a lot of business applications for voiceprint recognition, the technology has get more and more attention of science and market. Extracting more robust speech feature parameters is the major aspect to develop the voiceprint recognition algorithm speed and correct rate. With the recording voice library in the laboratory, the paper extracted Mel frequency cepstrum coefficient and its difference, weighted cepstrum coefficient. Then get new hybrid parameters composed of parameter vector with high Importance based on analysis of increase and decrease component. Finally, the paper build a speaker recognition model based on the VQ and designed different codebook capacity experiments with the LBG algorithm. Experimental results show that hybrid parameters through this paper's analysis got a higher recognition rate in the speaker recognition.