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This paper proposes a single-channel speech enhancement method to reduce thenoise and enhance speech at low signal-to-noise ratio (SNR) levels andnon-stationary noise conditions. Specifically, we focus on modeling the noiseusing a Gaussian mixture model (GMM) based on a multi-stage process with aparametric Wiener filter. The proposed noise model estimates a more accuratenoise power spectral density (PSD), and allows for better generalization undervarious noise conditions compared to traditional Wiener filtering methods.Simulations show that the proposed approach can achieve better performance interms of speech quality (PESQ) and intelligibility (STOI) at low SNR levels.

GMM based multi-stage Wiener filtering for low SNR speech enhancement