小波网络和RBF网络的抗噪语音识别  

Noise-robust speech recognition based on wavelet network and RBF network

作　　者：侯雪梅[1] 

机构地区：[1]西安邮电学院信息与控制系,西安710121

出　　处：《计算机工程与应用》2009年第19期150-152,共3页Computer Engineering and Applications

基　　金：西安邮电学院中青年教师项目科研基金(No.110-0417)

摘　　要：针对目前在噪音环境下语音识别系统性能较差的问题,利用小波神经网络融合了小波变换良好的时频局域化性质和RBF神经网络具有最佳分类能力和辨识能力等特性。构建了一个用小波基替代RBF网络中激活函数的小波-RBF神经网络结构,并采用全监督训练算法,实现了基于小波-RBF网络的抗噪语音识别系统。实验结果表明该系统比RBF网络具有更好的识别效果,尤其在噪声环境下,具有更强的鲁棒性。To solve the problem that recognition rates of speech recognition systems decrease in the nmsy environment presently, uses character possessing wavelet neural network which integrates the good time-field local property of wavelet transform,uses character possessing RBF neural network,which have best classification ability and recognize ability etc.This paper construetes a wavelet-RBF neural network structure using Morlet mother-wavelet as wavelet basis stead of activate function in the RBF network,adopts whole supervision algorithm and realizes a noise-robust speech recognition system based on wavelet network RBF net-work.The experiment results show that the system has better identify effect than RBF network especially has stronger Robust under noisy environment.

关 键 词：语音识别 RBF神经网络 小波神经网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]