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In the context of noise reduction algorithms, three instrumental measures are of major interest: the speech component quality, the level of noise attenuation, and noise distortion in terms of musical tones. As several proposals are made for the first two, the amount of musical tones is commonly still subjectively evaluated. Recent exploration of the log-kurtosis ratio for instrumentally measuring...
Several investigations showed that speech enhancement approaches can be improved by speech presence uncertainty (SPU) estimation. Although there has been a strong focus on the use of correct statistical models for spectral weighting rules for the last few decades, there is just a few publications about SPU estimation based on a speech prior consistent with the spectral weighting rule. This contribution...
In many applications non-stationary Gaussian or stationary non-Gaussian 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...
In many applications non-Gaussian noises, such as babble noise, can be observed. In this paper we present a minimum mean square error (MMSE) estimation of the speech spectral amplitude. It principally allows for arbitrary speech spectral amplitude probability density function (pdf) models (Rayleigh, Chi, …), while the pdf of the noise DFT coefficients is modeled by a Gaussian mixture (GMM). Applying...
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