Speech Endpoint Detection Algorithm Analyses Based on Short-term Energy
Huijuan Cui · Audio Engineering · 2005
This paper analyzes speech endpoint detection based on short-term energy feature in the presence of noise. Besides short-term full band energy feature, short-term high band energy is employed as an accessorial feature in the proposed algorithm. It also uses an optimal edge detection filter plus a three-state transition and judgment mechanism based on double thresholds, which ensure the accuracy in noisy environment and the robustness to changes in absolute levels. Experiments show that the proposed algorithm outperforms traditional energy threshold and G.729 VAD for speech endpoint detection in noisy environments and proves its accuracy, simplicity and robustness.