Robust Speech Recognition Based on Human Binaural Perception

In this paper we present a new method of signal processing for robust speech recognition using multiple microphones. The method, based on human binaural hearing, consists of passing the speech signals detected by multiple microphones through bandpass filtering and nonlinear rectification operations, and then cross-correlating the outputs from each channel within each frequency band. These operations provide an estimate of the energy contained in the speech signal in each frequency band, and provides rejection of off-axis jamming noise sources. We demonstrate that this method increases recognition accuracy for a multi-channel signal compared to equivalent processing of a monaural signal, and compared to processing using simple delay-and-sum beamforming.