An algorithm suitable for voice activity detection under reverberant conditions is proposed in this paper. Due to the use of far-filed microphones the proposed solution processes speech signals of highly-varying intensity and signal to noise ratio, that are contaminated with several echoes. The core of the system is a pair of Hidden Markov Models, that effectively model the speech presence and speech absence situations. To minimise mis-detections an adaptive threshold is used, while a hang-over scheme caters for the intra-frame correlation of speech signals. Experimental results conducted in a typical office room using a single far field microphone to support the analysis.
Dsp 2009: 16th International Conference on Digital Signal Processing, Proceedings, 2009, p. 1-5
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DSP 2009: 16th International Conference on Digital Signal Processing