Fast distributed multichannel speech enhancement using novel frequency domain estimators of magnitude-squared spectrum

Abstract

This paper proposes two novel frequency domain estimators for fast distributed multichannel speech enhancement in background of white and colored noise. The proposed two frequency domain estimators are maximum a posterior (MAP) and minimum mean square error (MMSE) estimators, respectively. They significantly generalize two single channel optimal frequency domain estimators of magnitude-squared spectrum. Compared with the optimal multichannel frequency domain estimator generalizing the single channel short-time spectral amplitude and log-spectral amplitude estimators, the proposed two frequency domain estimators have a very low computational cost. Computed results show that the proposed two estimators reduce both colored background noise and speech distortion. Furthermore, the proposed two multichannel algorithms have a much faster computational speed than conventional multichannel algorithms for distributed multichannel speech enhancement.