基于频谱方差和谱减法的语音端点检测新算法

New speech endpoint detection algorithm based on spectrum variance and spectral subtraction

针对低信噪比情况下频谱方差法对语音信号进行端点检测时准确率降低的问题,提出了一种结合频谱方差和谱减法的语音端点检测新算法。算法采用改进的谱减法对语音信号进行动态降噪处理,并依据得到的降噪后信号的频谱方差设置双门限值进行端点检测。仿真实验表明,该方法具有抗噪性好、自适应性强等优点,在低信噪比情况下检测的准确率与普通的频谱方差法相比有很大的提高。

In order to improve correctness of endpoint detection method based on spectrum variance in the case of low Signal Noise Rate（SNR）, this paper proposes a new speech endpoint detection algorithm based on combination spectrum variance with spectral subtraction. It reduces speech signal noise dynamically by using modified spectral subtraction and calculates its variance to set double-threshold in endpoint detection. Simulation results indicate that the proposed algo-rithm has advantages of high noise-robust and adaptive performance. Furthermore, it has better detection capability than spectrum variance method in the case of low SNR.