Efficient voice activity detection in reverberant enclosures using far field microphones

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.