Self-Supervised Denoising Autoencoder with Linear Regression Decoder for Speech Enhancement

Nonlinear spectral mapping-based models based on supervised learning have successfully applied for speech enhancement. However, as supervised learning approaches, a large amount of labelled data (noisy-clean speech pairs) should be provided to train those models. In addition, their performances for...

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Vydané v:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) s. 6669 - 6673
Hlavní autori:	Zezario, Ryandhimas E., Hussain, Tassadaq, Lu, Xugang, Wang, Hsin-Min, Tsao, Yu
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.05.2020
Predmet:	Decoding deep denoising autoencoder Linear regression Noise measurement Noise reduction Speech enhancement Supervised learning Task analysis unsupervised learning
ISSN:	2379-190X
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