Detail publikace

Joint audio denoising and inpainting with plug-and-play proximal algorithm

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

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"
}