Publication result detail

Psychoacoustically motivated audio declipping based on weighted l1 minimization

ZÁVIŠKA, P.; RAJMIC, P.; SCHIMMEL, J.

Original Title

Psychoacoustically motivated audio declipping based on weighted l1 minimization

English Title

Psychoacoustically motivated audio declipping based on weighted l1 minimization

Type

Paper in proceedings (conference paper)

Original Abstract

A novel method for audio declipping based on sparsity is presented. The method incorporates psychoacoustic information by weighting the transform coefficients in the l1 minimization. Weighting leads to an improved quality of restoration while retaining a low complexity of the algorithm. Three possible constructions of the weights are proposed, based on the absolute threshold of hearing, the global masking threshold and on a quadratic curve. Experiments compare the restoration quality according to the signal-to-distortion ratio (SDR) and PEMO-Q objective difference grade (ODG) and indicate that with correctly chosen weights, the presented method is able to compete, or even outperform, the current state of the art.

English abstract

A novel method for audio declipping based on sparsity is presented. The method incorporates psychoacoustic information by weighting the transform coefficients in the l1 minimization. Weighting leads to an improved quality of restoration while retaining a low complexity of the algorithm. Three possible constructions of the weights are proposed, based on the absolute threshold of hearing, the global masking threshold and on a quadratic curve. Experiments compare the restoration quality according to the signal-to-distortion ratio (SDR) and PEMO-Q objective difference grade (ODG) and indicate that with correctly chosen weights, the presented method is able to compete, or even outperform, the current state of the art.

Keywords

Declipping; Psychoacoustics; Restoration; Sparsity

Key words in English

Declipping; Psychoacoustics; Restoration; Sparsity

Authors

ZÁVIŠKA, P.; RAJMIC, P.; SCHIMMEL, J.

RIV year

2020

Released

01.07.2019

Publisher

IEEE

Location

Budapest, Hungary

ISBN

978-1-7281-1864-2

Book

Proceedings of the 2019 42nd International Conference on Telecommunications and Signal Processing (TSP)

Pages from

338

Pages to

342

Pages count

5

BibTex

@inproceedings{BUT156218,
  author="Pavel {Záviška} and Pavel {Rajmic} and Jiří {Schimmel}",
  title="Psychoacoustically motivated audio declipping based on weighted l1 minimization",
  booktitle="Proceedings of the 2019 42nd International Conference on Telecommunications and Signal Processing (TSP)
",
  year="2019",
  pages="338--342",
  publisher="IEEE",
  address="Budapest, Hungary",
  doi="10.1109/TSP.2019.8769109",
  isbn="978-1-7281-1864-2"
}

Documents

107