Publication detail

Audio Inpainting: Revisited and Reweighted

MOKRÝ, O. RAJMIC, P.

Original Title

Audio Inpainting: Revisited and Reweighted

Type

journal article in Web of Science

Language

English

Original Abstract

In this article, we deal with the problem of sparsity-based audio inpainting, i.e. filling in the missing segments of audio. A consequence of the approaches based on mathematical optimization is the insufficient amplitude of the signal in the filled gaps. Remaining in the framework based on sparsity and convex optimization, we propose improvements to audio inpainting, aiming at compensating for such an energy loss. The new ideas are based on different types of weighting, both in the coefficient and the time domains. We show that our propositions improve the inpainting performance in terms of both the SNR and ODG.

Keywords

audio inpainting; sparse representations; proximal algorithms; Douglas–Rachford algorithm; Chambolle–Pock algorithm; energy loss compensation; amplitude drop

Authors

MOKRÝ, O.; RAJMIC, P.

Released

13. 10. 2020

Publisher

IEEE

ISBN

2329-9290

Periodical

IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH AND LANGUAGE PROCESSING

Number

28

State

United States of America

Pages from

2906

Pages to

2918

Pages count

13

URL

https://ieeexplore.ieee.org/document/9222235

BibTex

@article{BUT164794,
  author="Ondřej {Mokrý} and Pavel {Rajmic}",
  title="Audio Inpainting: Revisited and Reweighted",
  journal="IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH AND LANGUAGE PROCESSING",
  year="2020",
  number="28",
  pages="2906--2918",
  doi="10.1109/TASLP.2020.3030486",
  issn="2329-9290",
  url="https://ieeexplore.ieee.org/document/9222235"
}