Voice Activity Detection Based on Wavelet Packet Transform and Adaptive Threshold
Hua Li · Jisuanji fangzhen · 2009
Voice activity detection is a crucial part in speech processing.Some traditional detection methods are ineffective in low SNR.To improve the performance and robustness,a new voice activity detection algorithm based on wavelet packet transform and adaptive threshold is proposed for the situation with white noise environment.The critical sub-band signals are obtained by wavelet packet transform,then smoothing the TEO of corresponding wavelet coefficients to enhance the discrimination capability of speech components,and lastly the adaptive threshold judgement is carried out.The experimental results prove that the new algorithm can efficiently distinguish the beginning and end points of voice segments in very low SNR environments.