Vector quantization based on the dynamic threshold of speaker recognition
基于动态阈值失量量化的说话人识别

Code splitting threshold is one of the important factors to initialize codebook in Speaker Recognition based on the Vector Quantitation (VQ), but traditional threshold is not easy to determine and needs a large number of experiments to determine the value. This paper used dynamic and random method to select the threshold in a certain range, and combined with differential cepstrum thresholds to establish speaker recognition model. The results show that given the method improves the recognition rate, the training time and the recognition time have improved significantly.