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Conference Papers Year : 2011

A Reproducible Research Framework for Audio Inpainting

Abstract

We introduce a unified framework for the restoration of distorted audio data, leveraging the Image Inpainting concept and covering existing audio applications. In this framework, termed Audio Inpainting, the distorted data is considered missing and its location is assumed to be known. We further introduce baseline approaches based on sparse representations. For this new audio inpainting concept, we provide reproducible-research tools including: the handling of audio inpainting tasks as inverse problems, embedded in a frame-based scheme similar to patch-based image processing; several experimental settings; speech and music material; OMP-like algorithms, with two dictionaries, for general audio inpainting or specifically-enhanced declipping.
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Dates and versions

inria-00587688 , version 1 (20-06-2011)

Identifiers

  • HAL Id : inria-00587688 , version 1

Cite

Amir Adler, Valentin Emiya, Maria G. Jafari, Michael Elad, Rémi Gribonval, et al.. A Reproducible Research Framework for Audio Inpainting. Workshop on Signal Processing with Adaptive Sparse Structured Representations, Jun 2011, Edinburgh, United Kingdom. ⟨inria-00587688⟩
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