Closely coupled array processing and model-based compensation for microphone array speech recognition

In this paper, a new microphone array speech recognition system in which the array processor and the speech recognizer are closely coupled is studied. The system includes a generalized sidelobe canceller (GSC) beamformer followed by a recognizer with vector Taylor series (VTS) compensation. The GSC beamformer provides two outputs, allowing more information to be used in the recognizer. One is the enhanced target speech output, the other is the reference noise output. VTS is used to compensate the effect of the residual noise in the GSC speech output, utilizing the GSC reference noise output. The compensation is done in a minimum mean square error (MMSE) sense. Moreover, an iteration procedure using an expectation-maximization (EM) algorithm is developed to refine the compensation parameters. Experimental results on the MONC database showed that the new system significantly improved the speech recognition performance in overlapping speech situations.