We propose a multi-channel speech dereverberation approach based on cross-channel cancellation and spectrogram decomposition. The reverberation is modeled as a convolution operation in the spectrogram magnitude domain. Using the Itakura divergence (I-divergence), we decompose reverberant spectrogram into clean spectrogram convolved with a deconvolution filter. The speech spectrogram is constrained and regularized by non-negativity and sparsity, respectively, while the deconvolution filter is constrained by non-negativity and cross-channel cancellation. Spectrogram decomposition of individual channels and cross-channel cancellation are jointly optimized by a multiplicative algorithm to achieve multi-channel speech dereverberation. We confirm through experiment that the proposed multi-channel method outperforms the related other single/multi-channel methods.

Index Terms: Multichannel dereverberation, Spectral decomposition, I-divergence, Sparsity, Cross-channel cancellation