Detail publikačního výsledku

Tweaking autoregressive methods for inpainting of gaps in audio signals

MOKRÝ, Ondřej; RAJMIC, Pavel

Originální název

Tweaking autoregressive methods for inpainting of gaps in audio signals

Anglický název

Tweaking autoregressive methods for inpainting of gaps in audio signals

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

A novel variant of the Janssen method for audio inpainting is presented and compared to other popular audio inpainting methods based on autoregressive (AR) modeling. Both conceptual differences and practical implications are discussed. The experiments demonstrate the importance of the choice of the AR model estimator, window/context length, and model order. The results show the superiority of the proposed gap-wise Janssen approach using objective metrics, which is confirmed by a listening test.

Anglický abstrakt

A novel variant of the Janssen method for audio inpainting is presented and compared to other popular audio inpainting methods based on autoregressive (AR) modeling. Both conceptual differences and practical implications are discussed. The experiments demonstrate the importance of the choice of the AR model estimator, window/context length, and model order. The results show the superiority of the proposed gap-wise Janssen approach using objective metrics, which is confirmed by a listening test.

Klíčová slova

audio; autoregression; inpainting; interpolation; comparison; packet loss concealment

Klíčová slova v angličtině

audio; autoregression; inpainting; interpolation; comparison; packet loss concealment

Autoři

MOKRÝ, Ondřej; RAJMIC, Pavel

Rok RIV

2026

Vydáno

08.09.2025

ISBN

978-9-46-459362-4

Kniha

2025 33rd European Signal Processing Conference (EUSIPCO)

Strany od

311

Strany do

315

Strany počet

5

URL

https://ieeexplore.ieee.org/document/11226154

BibTex

@inproceedings{BUT198878,
  author="Ondřej {Mokrý} and Pavel {Rajmic}",
  title="Tweaking autoregressive methods for inpainting of gaps in audio signals",
  booktitle="2025 33rd European Signal Processing Conference (EUSIPCO)",
  year="2025",
  pages="311--315",
  doi="10.23919/EUSIPCO63237.2025.11226154",
  isbn="978-9-46-459362-4",
  url="https://ieeexplore.ieee.org/document/11226154"
}