Speech endpoint detection based on recurrence rate analysis

In order to perform speech endpoint detection under extreme noisy and nonstationary conditions,a new algorithm based on the difference of underlying dynamics between speech and noise was proposed.Recurrence rate was taken as the quantification parameter to measure the variation of such difference and double decision thresholds were applied in the deci-sion framework.Comparing with some traditional methods such as short-time energy and cepstral distances,this algorithm shows lower wrong decision rate.This method provides a new way for feature extraction and speech recognition.