Audio inpainting: problem statement, relation with sparse representations and some experiments

Amir Adler 1 Valentin Emiya 2 Maria Jafari 3 Michael Elad 1 Rémi Gribonval 2 Mark Plumbley 3
2 METISS - Speech and sound data modeling and processing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : We propose a framework called audio inpainting for the general problem of estimating missing samples in audio. It extends the problem of the interpolation and extrapolation of signals to the cases where possibly-large blocks of consecutive samples must be estimated from the remaining, known samples. We relate this framework to a number of applications including declicking, declipping and audio packet loss in voice over IP. By considering audio inpainting as an inverse problem, we show that sparse representations are an appropriate scheme to develop new approaches for the audio inpainting problem. We will present some experiments, with a particular focus on restoration of clipped speech or music signals.
Type de document :
Poster
SMALL Workshop on Sparse Dictionary Learning, Jan 2011, London, United Kingdom. 2011
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https://hal.inria.fr/inria-00560110
Contributeur : Valentin Emiya <>
Soumis le : mercredi 7 décembre 2011 - 14:18:28
Dernière modification le : mercredi 16 mai 2018 - 11:23:03
Document(s) archivé(s) le : jeudi 8 mars 2012 - 02:20:26

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  • HAL Id : inria-00560110, version 1

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Amir Adler, Valentin Emiya, Maria Jafari, Michael Elad, Rémi Gribonval, et al.. Audio inpainting: problem statement, relation with sparse representations and some experiments. SMALL Workshop on Sparse Dictionary Learning, Jan 2011, London, United Kingdom. 2011. 〈inria-00560110〉

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