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Voice activity detection based on frequency modulation of harmonics

In this paper, we propose a voice activity detection (VAD) algorithm based on spectro-temporal modulation structures of input sounds. A multi-resolution spectro-temporal analysis framework is used to inspect prominent speech structures. By comparing with an adaptive threshold, the proposed VAD distinguishes speech from non-speech based on the energy of the frequency modulation of harmonics. Compared with three standard VADs, ITU-T G.729B, ETSI AMR1 and AMR2, our proposed VAD significantly outperforms them in non-stationary noises in terms of the receiver operating characteristic (ROC) curves and the recognition rates from a practical distributed speech recognition (DSR) system.