Speech Enhancement with Variational Autoencoders and Alpha-stable Distributions

This paper focuses on single-channel semi-supervised speech enhancement. We learn a speaker-independent deep generative speech model using the framework of variational autoencoders. The noise model remains unsupervised because we do not assume prior knowledge of the noisy recording environment. In t...

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Vydané v:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) s. 541 - 545
Hlavní autori:	Leglaive, Simon, Simsekli, Umut, Liutkus, Antoine, Girin, Laurent, Horaud, Radu
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.05.2019
Predmet:	alpha-stable distribution Context modeling Deep learning Expectation-maximization algorithms Monte Carlo expectation-maximization Monte Carlo methods Noise measurement Speech enhancement Time-frequency analysis variational autoencoders
ISSN:	2379-190X
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