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.
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https://hal.inria.fr/inria-00545480
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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. 9th Int. Conf. on Latent Variable Analysis and Signal Separation, Sep 2010, Saint-Malo, France. 2010. ⟨inria-00545480⟩

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