Robust Voice Activity Detection using Group Delay Functions

In this paper, we present an algorithm for Voice Activity Detection (VAD) in speech signals with very low SNR. In the proposed algorithm, the short-term energy of the speech signal is viewed as the positive frequency part of the magnitude spectrum of a minimum phase signal. The group delay of this signal is then computed. The speech regions of the signal are characterized by well-defined peaks in the group delay spectrum, while the non-speech regions are identified by well-defined valleys. The proposed method is compared experimentally with G.729 Annex B in very low SNR conditions with different types of noises and is found to perform significantly better.