基于LPC距离和变窗长的端点检测

Endpoint detection based on LPC distance and variable window length

基于LPC距离的端点检测首先会对信号进行分帧处理,然后根据LPC距离设置阈值依次判断每一帧是否为语音的端点。而在对信号进行分帧时会有以下问题:如果采用较大的窗长,则总帧数会变少,但是这样端点检测的误差也会增加,尤其是对于语音起点的检测。而如果帧长选取过小,则计算量增加,识别速度也会增加。针对这个问题,将变窗长思想和基于LPC距离端点检测算法结合起来,提出了一种改进的端点检测算法。该方法在分帧时不采用统一的窗长,而是在静音段采用大窗长快速向过渡段逼近,进入过渡段后采用小窗长慢慢寻找语音信号的起点,其他阶段则采用常规窗长。研究表明,所提出的改进的端点检测方法检测性能要优于其他两种端点检测方法。

Endpoint detection based on LPC distance will first frame the signal processing,and then according to the LPC distance set threshold to determine whether each frame is the endpoint of the voice.However,it will have the following questions in the signal frame：if a larger window length is used,the total number of frames will be reduced,but the error in the endpoint detection will also increase,especially for the detection of the origin of the speech.If the frame length selection is too small,the calculation amount and the recognition speed are increased.Aiming at this problem,this paper proposes an improved endpoint detection algorithm combining the variable window length idea with the LPC distance endpoint detection algorithm.The method does not use the uniform window length in the frame,but in the quiet section uses a large window length quickly approaching the transition section.Then after the transition,the small window length is used slowly to look for the starting point of the voice signal,the other stage is the use of conventional windows long.Simulation results show that the improved endpoint detection method proposed in this paper is superior to the other two endpoint detection methods.