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ŠVENTO, M. MOKRÝ, O.
Originální název
Joint audio denoising and inpainting with plug-and-play proximal algorithm
Typ
článek ve sborníku mimo WoS a Scopus
Jazyk
angličtina
Originální abstrakt
We propose plug-and-play variant of the Douglas–Rachford proximal algorithm for audio inpainting, which replaces a proximal step with a denoiser. In our situation, the observed samples are further degraded by noise. We demonstrate that the plug-and-play aproach has potential to succeed in this joint task of inpainting and denoising. Objective metrics show that the new method outperforms a conventional counterpart and that it is less sensitive to model hyperparameters.
Klíčová slova
speech enhancement; deep learning; denoising; Douglas–Rachford algorithm; inpainting
Autoři
ŠVENTO, M.; MOKRÝ, O.
Vydáno
25. 4. 2023
Nakladatel
Brno University of Technology, Faculty of Electrical Engineering and Communication
Místo
Brno
ISBN
978-80-214-6153-6
Kniha
Proceedings I of the 29th Student EEICT 2023 (General Papers)
Edice
1
Strany od
214
Strany do
217
Strany počet
5
URL
https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf
BibTex
@inproceedings{BUT184260, author="Michal {Švento} and Ondřej {Mokrý}", title="Joint audio denoising and inpainting with plug-and-play proximal algorithm", booktitle="Proceedings I of the 29th Student EEICT 2023 (General Papers)", year="2023", series="1", pages="214--217", publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication", address="Brno", isbn="978-80-214-6153-6", url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf" }