A study on subspace-based estimation of STFT real and imaginary modulation signals for speech enhancement

Abstract

In this paper, we investigate the advantages of applying the subspace approach within short-time Fourier transform-based (STFT) modulation domains over the conventional sub-space algorithm for single-channel speech enhancement. Specifically, we consider the subspace processing of the modulations of STFT real and imaginary (RI) parts and the modulations of the STFT magnitude values. Speech enhancement experiments were performed on the Noizeus speech corpus that had been corrupted by varying levels of white and coloured noise. The results indicate that the modulation domain-based subspace methods outperformed the conventional subspace approach in both enhanced speech quality and intelligibility. Objectively, the RI-modulation subspace method was found to have a slight quality and intelligibility advantage over the magnitude modulation subspace method. In blind subjective testing on speech quality, the modulation subspace methods were significantly preferred over the conventional time-domain-based subspace method.