基于VQ的说话人识别系统的实现

The Realization of the Speaker Recognition System Based on VQ

系统以语音信号的LPC倒谱系数、差值倒谱系数、基音周期和差值基音周期的混合特征参数作为识别的特征矢量集,运用矢量量化(VQ)技术实现了与文本有关的说话人识别。在一个10人,1800个语音的语音库上进行了系统的识别实验,其中单音节语音的平均识别率达到了92%,双音节语音达到了96.67%,四音节语音达到了97.67%。系统用于实时识别也收到了较好的效果。

This paper is mainly about a text-dependent speaker recognition system based on vector quantification (VQ) methods. We use LPC-derived cepstral coefficients, delta-cepstral coefficients, pitches and delta-pitches as the feature parameter set. Through the test of a speech library composed of 10 speakers and 1800 speeches, we get the fairly high recognition rate, which is about 92% for one-syllable words, about 96.67% for two-syllable words and about 97.67% for four-syllable words. This system can also be used in the real-time speaker recognition.