Introducing a simple fusion framework for audio source separation

Abstract : We propose in this paper a simple fusion framework for underdetermined audio source separation. This framework can be applied to a wide variety of source separation algorithms providing that they estimate time-frequency masks. Fusion principles have been successfully implemented for classification tasks. Although it is similar to classification, audio source separation does not usually take advantage of such principles. We thus introduce some general fusion rules inspired by classification and we evaluate them in the context of voice extraction. Experimental results are promising as our proposed fusion rule can improve separation results up to 1 dB in SDR.
Type de document :
Communication dans un congrès
2013 IEEE International Workshop on Machine Learning for Signal Processing, Sep 2013, Southampton, United Kingdom. pp.6, 2013
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-00846834
Contributeur : Xabier Jaureguiberry <>
Soumis le : dimanche 21 juillet 2013 - 19:54:56
Dernière modification le : lundi 25 février 2019 - 11:08:10
Document(s) archivé(s) le : mardi 22 octobre 2013 - 04:19:39

Fichier

mlsp2013_vHal.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00846834, version 1

Citation

Xabier Jaureguiberry, Gaël Richard, P. Leveau, Romain Hennequin, Emmanuel Vincent. Introducing a simple fusion framework for audio source separation. 2013 IEEE International Workshop on Machine Learning for Signal Processing, Sep 2013, Southampton, United Kingdom. pp.6, 2013. 〈hal-00846834〉

Partager

Métriques

Consultations de la notice

601

Téléchargements de fichiers

235