Revisiting synthesis model in Sparse Audio Declipper
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU127599" target="_blank" >RIV/00216305:26220/18:PU127599 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/book/10.1007%2F978-3-319-93764-9" target="_blank" >https://link.springer.com/book/10.1007%2F978-3-319-93764-9</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-93764-9_40" target="_blank" >10.1007/978-3-319-93764-9_40</a>
Alternative languages
Result language
angličtina
Original language name
Revisiting synthesis model in Sparse Audio Declipper
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20203 - Telecommunications
Result continuities
Project
<a href="/en/project/GF17-33798L" target="_blank" >GF17-33798L: Modern restoration of lost information in digital audio</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Latent Variable Analysis and Signal Separation, 14th International Conference, LVA/ICA 2018 Proceedings
ISBN
978-3-319-93764-9
ISSN
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e-ISSN
—
Number of pages
17
Pages from-to
429-445
Publisher name
Springer
Place of publication
Cham
Event location
Guildford
Event date
Jul 2, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000521730400040