Speech enhancement in modulation domain using codebook-based speech and noise estimation

Abstract

Conventional single-channel speech enhancement methods implement the analysis-modification-synthesis (AMS) framework in the acoustic frequency domain. In recent years, it has been shown that the extension of this framework to the modulation frequency domain may result in better noise suppression. However, this conclusion has been reached by relying on a minimum statistics approach for the required noise power spectral density (PSD) estimation, which is known to create a time frame lag when the noise is non-stationary. In this paper, to avoid this problem, we perform noise suppression in the modulation domain with speech and noise power spectra obtained from a codebook-based estimation approach. The PSD estimates derived from the codebook approach are used to obtain a minimum mean square error (MMSE) estimate of the clean speech modulation magnitude spectrum, which is combined with the phase spectrum of the noisy speech to recover the enhanced speech signal. Results of objective evaluations indicate improvement in noise suppression with the proposed codebook-based speech enhancement approach, particularly in cases of non-stationary noise.1