关键词: 小波分析（WA）, 支持向量机（SVM）, 遗传算法（GA）, 语音端点检测

Abstract: Speech endpoint detection is one of the important links of speech recognition system. In view of the question that the speech endpoint detection is difficult in noisy environment, this paper proposes a kind of speech endpoint detection method based on improved Support Vector Machine（SVM）. First, it extracts the feature vector of the noisy speech signal using the Wavelet Analysis（WA）. Then, it gets the optimal parameters of the SVM kernel function [γ] and penalty factor [C] using the Genetic Algorithm（GA）. Finally, it establishes speech endpoint detection model. Carried out the simulation experiments in the Matlab software platform, the results show that the average detection rate of GA-SVM is 94.5% under the condition of different noise. It is superior to the traditional double threshold algorithm and ordinary SVM algorithm.

Key words: Wavelet Analysis（WA）, Support Vector Machine（SVM）, Genetic Algorithm（GA）, speech endpoint detection