Detail publikace

Revisiting synthesis model in Sparse Audio Declipper

ZÁVIŠKA, P. RAJMIC, P. PRŮŠA, Z. VESELÝ, V.

Originální název

Revisiting synthesis model in Sparse Audio Declipper

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The state of the art in audio declipping has currently been achieved by SPADE (SParse Audio DEclipper) algorithm by Kitic et al. Until now, the synthesis/sparse variant, S-SPADE, has been considered significantly slower than its analysis/cosparse counterpart, A-SPADE. It turns out that the opposite is true: by exploiting a recent projection lemma, individual iterations of both algorithms can be made equally computationally expensive, while S-SPADE tends to require considerably fewer iterations to converge. In this paper, the two algorithms are compared across a range of parameters such as the window length, window overlap and redundancy of the transform. The experiments show that although S-SPADE typically converges faster, the average performance in terms of restoration quality is not superior to A-SPADE.

Klíčová slova

Clipping, Declipping, Audio, Sparse, Cosparse, SPADE, Projection, Restoration

Autoři

ZÁVIŠKA, P.; RAJMIC, P.; PRŮŠA, Z.; VESELÝ, V.

Vydáno

2. 7. 2018

Nakladatel

Springer

Místo

Cham

ISBN

978-3-319-93764-9

Kniha

Latent Variable Analysis and Signal Separation, 14th International Conference, LVA/ICA 2018 Proceedings

Edice

Lecture Notes in Computer Science

Číslo edice

10891

Strany od

429

Strany do

445

Strany počet

17

URL

BibTex

@inproceedings{BUT146951,
  author="Pavel {Záviška} and Pavel {Rajmic} and Zdeněk {Průša} and Vítězslav {Veselý}",
  title="Revisiting synthesis model in Sparse Audio Declipper",
  booktitle="Latent Variable Analysis and Signal Separation, 14th International Conference, LVA/ICA 2018 Proceedings",
  year="2018",
  series="Lecture Notes in Computer Science",
  number="10891",
  pages="429--445",
  publisher="Springer",
  address="Cham",
  doi="10.1007/978-3-319-93764-9\{_}40",
  isbn="978-3-319-93764-9",
  url="https://link.springer.com/book/10.1007%2F978-3-319-93764-9"
}