Audio declipping via nonnegative matrix factorization
| Autor: | Patrick Pérez, Alexey Ozerov, Cagdas Bilen |
|---|---|
| Přispěvatelé: | Technicolor [Cesson Sévigné], Technicolor, ANR-14-CE27-0002,MAD,Inpainting de données audio manquantes(2014), Ozerov, Alexey, Appel à projets générique - Inpainting de données audio manquantes - - MAD2014 - ANR-14-CE27-0002 - Appel à projets générique - VALID |
| Rok vydání: | 2015 |
| Předmět: |
Audio inpainting
Signal processing Audio signal Noise measurement [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing business.industry Speech recognition nonneg-ative matrix factorization audio declipping Inpainting generalized expectation-maximization Pattern recognition computer.software_genre Itakura-Saito divergence Matrix decomposition Non-negative matrix factorization [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Source separation Artificial intelligence Audio signal processing business computer Mathematics |
| Zdroj: | WASPAA IEEE Workshop on Applications of Signal Processing to Audio and Acoustics IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, Oct 2015, New Paltz, NY, United States |
| DOI: | 10.1109/waspaa.2015.7336948 |
| Popis: | International audience; Audio inpainting and audio declipping are important problems in audio signal processing, which are encountered in various practical applications. A number of approaches has been proposed in the literature to address these problems, most successful of which are based on sparsity of the audio signals in certain dictionary representations. Non-negative matrix factorization (NMF) is another powerful tool that has been successfully used in applications such as audio source separation. In this paper we propose a new algorithm that makes use of a low rank NMF model to perform audio inpainting and declipping. In addition to utilizing for the first time the NMF model to perform audio inpainting in presence of arbitrary losses in time domain, the proposed approach also introduces a novel way to enforce additional constraints on the signal magnitude in order to improve the performance in declipping applications. The proposed approach is shown to have a comparable performance with the state of the art dictionary based methods while providing a number of advantages. |
| Databáze: | OpenAIRE |
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