This paper addresses the problem of robust voice activity detection (VAD) capable for working at very low signal-to-noise ratios (SNR<10dB). A new algorithm that we propose is based on entropy estimation measures of the time-frequency magnitude spectrum. The problem of the estimation of the distribution of noise in detected non-speech segments of analysed signal is also presented. It is shown that the new entropy based VAD significantly outperforms the commonly used energy-based algorithms in all (stationary, non-stationary, white and coloured) noise conditions at SNRs from 10 dB down to -10 dB and below. One of the main advantages of the method proposed in this paper is that it is not very sensitive to the changing level of noise.
Cite as: Renevey, P., Drygajlo, A. (2001) Entropy based voice activity detection in very noisy conditions. Proc. 7th European Conference on Speech Communication and Technology (Eurospeech 2001), 1887-1890, doi: 10.21437/Eurospeech.2001-446
@inproceedings{renevey01b_eurospeech,
author={Philippe Renevey and Andrzej Drygajlo},
title={{Entropy based voice activity detection in very noisy conditions}},
year=2001,
booktitle={Proc. 7th European Conference on Speech Communication and Technology (Eurospeech 2001)},
pages={1887--1890},
doi={10.21437/Eurospeech.2001-446}
}