一种新的基于信息熵的带噪语音端点检测方法

在自动语音识别和变速率语音编码技术中,语音端点检测是前端处理的一个重要环节.而在实际的噪声环境下,一些传统的端点检测方法已不适用.该文提出了一种新的基于信息熵的语音端点检测方法,该方法通过对语音信号的短时功率谱进行谱分析,由此构造熵函数作为端点检测的特征参数.实验结果表明,该方法在噪声环境下性能优于传统的基于能量的端点检测方法.而且相对于基于频谱谱熵的算法,在低信噪比（SNR〈0dB）情况下,该文方法有更好的鲁棒性,可使平均检测精确度进一步提高约5%.

A Novel Approach to Entropy-based Endpoint Detection of Noisy Speech

In the technology of speech recognition and variable bit rate speech coding,accurate determination of speech is a crucial part.Some traditional endpoint detection methods are ineffective in real noisy environments.This paper presents a novel entropy-based approach to speech endpoint detection.In the proposed method,we analyze the short-term power spectrum of speech signal,from which the entropy is derived and used as a feature in endpoint detection.Experimental results show that this method outperforms the traditional energy-based methods.Compared with the spectral entropy-based algorithm ~(1]),it possesses a better robustness in low SNR environments(SNR<0dB) and can improve the precision of endpoint detection about 5%.