Multi-microphone speech dereverberation based on eigen-decomposition: A study

Sharon Gannot

Abstract: A family of approaches for multi-microphone speech dereverbera- tion in colored noise environments, which uses the eigen-decomposition of the data correlation matrix, is studied in this paper. A recently proposed method shows that the Room Impulse Response (RIR)s, relating the speech source and the microphones, are embedded in the null subspace of the received signals. In cases where the channel order is overestimated, a closed-form algorithm for extracting the RIR is proposed. A variant, in which the sub- space method is incorporated into a subband framework, is given as well. In the last stage of the proposed method, the desired signal is reconstructed, using the estimated RIRs, by applying either the Matched Filter Beamformer (MBF) or the Multi-channel Inverse filter Theorem (MINT) algorithms. The emphasis of the current work is a comprehensive experimental study of the eigen-decomposition based dereverberation methods and the required channel inversion algorithms. This study supports the potential of the presented method, and provides insight into its limitations.