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ICASSP
2011
IEEE

Speech enhancement using a joint map estimator with Gaussian mixture model for (non-)stationary noise

12 years 7 months ago
Speech enhancement using a joint map estimator with Gaussian mixture model for (non-)stationary noise
In many applications non-stationary Gaussian or stationary nonGaussian noises can be observed. In this paper we present a maximum a posteriori estimation jointly of spectral amplitude and phase (JMAP). It principally allows for arbitrary speech models (Gaussian, super-Gaussian, ...), while the noise DFT coefficients pdf is modeled as Gaussian mixture (GMM). Such a GMM covers both a non-Gaussian stationary noise process, but also a non-stationary process that changes between Gaussian noise modes of different variance with probability of the GMM weight. Accordingly, we provide results for these two types of noise, showing superiority over the Gaussian noise model JMAP estimator even in case of ideal noise power estimation.
Balázs Fodor, Tim Fingscheidt
Added 20 Aug 2011
Updated 20 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Balázs Fodor, Tim Fingscheidt
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