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arXiv · 1807.03612

Revisiting Synthesis Model of Sparse Audio Declipper

Pavel Záviška·Pavel Rajmic·Zdeněk Průša·Vítězslav Veselý
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Abstract

The state of the art in audio declipping has currently been achieved by SPADE (SParse Audio DEclipper) algorithm by Kitić 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.

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BibTeXRIS

Pavel Záviška, Pavel Rajmic, Zdeněk Průša, Vítězslav Veselý. 2018-07-11. Revisiting Synthesis Model of Sparse Audio Declipper. https://doi.org/10.1007/978-3-319-93764-9_40

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