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• W2171048182 abstract "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 for both approaches an idealized a priori SNR estimator that works well in babble noise, we can show clear improvements compared to the MMSE spectral amplitude estimator with Gaussian noise assumption." @default.
• W2171048182 created "2016-06-24" @default.
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• W2171048182 date "2011-08-29" @default.
• W2171048182 modified "2023-09-25" @default.
• W2171048182 title "MMSE speech spectral amplitude estimation assuming non-Gaussian noise" @default.
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• W2171048182 doi "https://doi.org/10.5281/zenodo.42434" @default.
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