Robust Voice Activity Detection Based on Discrete Wavelet Transform

Robust Voice Activity Detection Based on Discrete Wavelet Transform

This paper mainly addresses the problem of determining voice activity in presence of noise, especially in a dynamically varying background noise. The proposed voice activity detection algorithm is based on structure of three-layer wavelet decomposition. Appling auto-correlation function into each subband exploits the fact that intensity of periodicity is more significant in sub-band domain than that in full-band domain. In addition, Teager energy operator (TEO) is used to eliminate the noise components from the wavelet coefficients on each subband. Experimental results show that the proposed wavelet-based algorithm is prior to others and can work in a dynamically varying background noise.