【作者】 白莹；

【导师】 赵振东；

【作者基本信息】 华北电力大学（河北） ， 通信与信息系统， 2005， 硕士

【摘要】 说话人识别是根据人的声音来识别人的身份的一种生物认证技术,广泛应用于人机接口、保安、军事、司法等方面。本文详细介绍了语音信号预处理、端点检测和特征提取的方法,建立了用BP 神经网络作为分类器的说话人识别系统。在此基础之上,将小波神经网络的模型引入到识别系统中。实际测试试验表明,基于小波神经网络的识别系统与基于BP 神经网络的识别系统相比,网络训练速度加快,识别率也有所提高,是说话人识别的一种有效可行的新方法。更多还原

【Abstract】 Speaker recognition is a biometrics that the identifier of a person can be recognized via his voice. It is applied to man-machine interface, ensure public security, military affairs, judicature, and so on. Speech signal pre-procession, point detection, feature extraction were discussed. Speaker recognition system based on BP neural network was set up. And then, the model of wavelet neural network was presented. The speaker recognition system using wavelet neural network as the classifier is constructed in this paper. The experiment results show that the proposed methods have faster training speed and higher recognition rate than the system based on BP neural network. The system based on wavelet neural network is useful and effective in speaker recognition.更多还原