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.

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