Distant Speech Recognition In Reverberant Noisy Conditions Employing A Microphone Array
Signal Processing Conference(2014)
Abstract
This paper addresses the problem of distant speech recognition in reverberant noisy conditions employing a microphone array. We present a prototype system that can segment the utterances in real-time and generate robust ASR results off-line. The segmentation is carried out by a voice activity detector based on deep belief networks, the speaker localization by a position-pitch plane, and the enhancement by a novel combination of convex optimized beamforming and vector Taylor series compensation. All of the components are compared with other similar ones and justified in terms of word accuracy on a proposed database which simulates distant speech recognition in a home environment.
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Key words
distant speech recognition,deep belief network voice activity detection,PoPi speaker localization,convex-optimized beamforming,vector Taylor series compensation,reverberant and noisy environment,natural mixing,German database
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