Publication detail

Revisiting synthesis model in Sparse Audio Declipper

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

Original Title

Revisiting synthesis model in Sparse Audio Declipper

Type

conference paper

Language

English

Original Abstract

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.

Keywords

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

Authors

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

Released

2. 7. 2018

Publisher

Springer

Location

Cham

ISBN

978-3-319-93764-9

Book

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

Edition

Lecture Notes in Computer Science

Edition number

10891

Pages from

429

Pages to

445

Pages count

17

URL

https://link.springer.com/book/10.1007%2F978-3-319-93764-9

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"
}