基于投影分类的语音端点检测方法

针对低信噪比条件下语音端点检测精度受噪声干扰严重的问题,提出了一种基于投影分类的语音端点检测方法。该方法首先利用长时语音信号变化率测度特征进行低信噪比环境中的语音特征计算,充分利用语音信号和非语音信号的不同来增强低信噪比条件下的区分度;接着,采用Fisher准则对语音和背景噪声进行分类识别,确保投影后的特征参数类内散度最小、类间散度最大。实验结果表明,方法具有较高的检测精度,在信噪比为-10 d B的白噪声干扰情况下仍然保持了86.7%以上的正确检测率。

Speech endpoint detection method based on projection classification

Aiming at the problem that the low SNR speech endpoint detection accuracy is seriously affected by the background,a speech endpoint detection method based on projection classification is proposed in this paper.Firstly,the phonetic characteristics of low SNR environment is calculated using long speech signal rate measure characteristics.The method makes full use of different speech signal and a voice signal to enhance the degree of differentiation of low SNR condition.Secondly,by using Fisher criterion,the classification identification of the voice and the background noise is carried out to ensure that the projection parameters have the smallest similar characteristics and the largest different characteristics.The experimental results show that the proposed method has high detection accuracy,the correct detection rate is more than 86.7％ even in the SNR =-10 dB white noise interference condition.