Latent-variable decomposition based dereverberation of monaural and multi-channel signals

We present an algorithm to dereverberate single- and multi-channel audio recordings. The proposed algorithm models the magnitude spectrograms of clean audio signals as histograms drawn from a multinomial process. Spectrograms of reverberated signals are obtained as histograms of draws from the PDF of the sum of two random variables, one representing the spectrogram of clean speech and the second the frequency decomposition of the room response. The spectrogram of the clean signal is computed as a maximum-likelihood estimate from the spectrogram of reverberant speech using an EM algorithm. Experimental evaluations show that the proposed algorithm is able to greatly reduce the reverberation effects in even highly reverberant signals captured in auditoria and other open spaces.