Detail publikace

Sparse and Cosparse Audio Dequantization Using Convex Optimization

Originální název

Sparse and Cosparse Audio Dequantization Using Convex Optimization

Anglický název

Sparse and Cosparse Audio Dequantization Using Convex Optimization

Jazyk

en

Originální abstrakt

The paper shows the potential of sparsity-based methods in restoring quantized signals. Following up on the study of Brauer et al. (IEEE ICASSP 2016), we significantly extend the range of the evaluation scenarios: we introduce the analysis (cosparse) model, we use more effective algorithms, we experiment with another time-frequency transform. The paper shows that the analysis-based model performs comparably to the synthesis-model, but the Gabor transform produces better results than the originally used cosine transform. Last but not least, we provide codes and data in a reproducible way.

Anglický abstrakt

The paper shows the potential of sparsity-based methods in restoring quantized signals. Following up on the study of Brauer et al. (IEEE ICASSP 2016), we significantly extend the range of the evaluation scenarios: we introduce the analysis (cosparse) model, we use more effective algorithms, we experiment with another time-frequency transform. The paper shows that the analysis-based model performs comparably to the synthesis-model, but the Gabor transform produces better results than the originally used cosine transform. Last but not least, we provide codes and data in a reproducible way.

Dokumenty

BibTex


@inproceedings{BUT164024,
  author="Pavel {Záviška} and Pavel {Rajmic}",
  title="Sparse and Cosparse Audio Dequantization Using Convex Optimization",
  annote="The paper shows the potential of sparsity-based methods in restoring quantized signals. Following up on the study of Brauer et al. (IEEE ICASSP 2016), we significantly extend the range of the evaluation scenarios: we introduce the analysis (cosparse) model, we use more effective algorithms, we experiment with another time-frequency transform. The paper shows that the analysis-based model performs comparably to the synthesis-model, but the Gabor transform produces better results than the originally used cosine transform. Last but not least, we provide codes and data in a reproducible way.",
  address="IEEE",
  booktitle="
Proceedings of the 2020 43rd International Conference on Telecommunications and Signal Processing (TSP)",
  chapter="164024",
  doi="10.1109/TSP49548.2020.9163566",
  howpublished="online",
  institution="IEEE",
  year="2020",
  month="august",
  pages="216--220",
  publisher="IEEE",
  type="conference paper"
}