基于短时平均能量和短时过零率的藏语语音端点检测研究

Research of Tibetan Speech Endpoint Detection Based on Short-term Average Anergy and Short-term Zero Rate Algorithm

语音端点检测是语音处理分析过程中的重要环节之一,该文介绍了语音端点检测的两个传统算法即短时平均能量和短时过零率,并将这两种算法结合起来进行藏语语音进行端点检测。运用Matlab编程和仿真验证了双门限判断法在藏语语音端点检测中的准确性。这种方法降低了藏语语音处理的时间、提高了处理的质量、可用来进行一些藏语语音识别的特征参数的提取。

Tibetan speech endpoint detection is an important part of Tibetan speech signal processing. This article introduced two traditional endpoint detection methods which including the short-term average energy and short-term zero rate algorithm and tested Tibetan speech endpoint detection by combing these two algorithm. It verified correctness of dual threshold method for the implementation of Tibetan speech endpoint detection.This method reduces the processing time and improve the quality for Tibetan speech Tibetan Speech Endpoint Detection.It can be used to extract some of the characteristics of Tibetan speech recognition parameters.