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A Constrained Matching Pursuit Approach to Audio Declipping

Amir Adler 1 Valentin Emiya 2 Maria Jafari 3 Michael Elad 1 Rémi Gribonval 2 Mark D. 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 present a novel sparse representation based approach for the restoration of clipped audio signals. In the proposed approach, the clipped signal is decomposed into overlapping frames and the declipping problem is formulated as an inverse problem, per audio frame. This problem is further solved by a constrained matching pursuit algorithm, that exploits the sign pattern of the clipped samples and their maximal absolute value. Performance evaluation with a collection of music and speech signals demonstrate superior results compared to existing algorithms, over a wide range of clipping levels.
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https://hal.inria.fr/inria-00557021
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Submitted on : Monday, February 21, 2011 - 9:55:05 AM
Last modification on : Friday, July 10, 2020 - 4:18:20 PM
Long-term archiving on: : Sunday, May 22, 2011 - 2:35:37 AM

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Amir Adler, Valentin Emiya, Maria Jafari, Michael Elad, Rémi Gribonval, et al.. A Constrained Matching Pursuit Approach to Audio Declipping. Acoustics, Speech and Signal Processing, IEEE International Conference on (ICASSP 2011), May 2011, Prague, Czech Republic. ⟨10.1109/ICASSP.2011.5946407⟩. ⟨inria-00557021⟩

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