摘要
在特定人语音识别系统中,噪声严重影响语音特征提取,并导致语音识别率明显下降。针对在噪声环境下语音识别率偏低的问题,通过谱减法去除语音信号噪声,并根据语音信号语谱图可视化的特点,运用脉冲耦合神经网络从语音信号的语谱图中提取熵序列作为特征参数进行语音识别。实验结果表明,该方法能较好地去除语音信号中的噪声,并能使在噪声环境下的特定人语音识别系统具有较好的识别效果。
For speaker dependent speech recognition,noise can seriously affect to the extraction of features,thus leads to low speech recognition rate.To address the issue,this paper applies spectral subtraction for de-noising.Based on the visualized features of speech spectrogram,the pulse coupled neural network is used to extract the feature parameters for the recognition system.Experiment results show that the proposed method can preferably reduce the noises and achieve a significantly improved recognition rate for a speaker dependent recognition task.
出处
《计算机工程与应用》
CSCD
2012年第3期133-136,共4页
Computer Engineering and Applications
关键词
语音识别
脉冲耦合神经网络
谱减法
speech recognition
pulse coupled neural network
spectral subtraction
