A Deep Learning Based Binaural Speech Enhancement Approach with Spatial Cues Preservation

Abstract

The studies of binaural hearing indicated considerable benefits of the spatial information of sound sources in speech understanding in noise. In this paper, we propose a binaural speech enhancement approach based on deep neural network. In this approach, the signals at the left and right channels are regarded as the real and imaginary parts of a monaural complex signal, a complex ideal ratio mask is accordingly introduced and then further estimated using the complex deep neural network, followed by applying to the monaural complex signal. Experimental results showed that the suggested binaural speech enhancement approach is able to effectively suppress multiple interfering signals and preserve the binaural cues of target signal.