Semi-Blind Student's t Source Separation for Multichannel Audio Convolutive Mixtures - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2017

Semi-Blind Student's t Source Separation for Multichannel Audio Convolutive Mixtures

Résumé

This paper addresses the problem of multichannel audio source separation in under-determined convolutive mixtures. We target a semi-blind scenario assuming that the mixing filters are known. The convolutive mixing process is exactly modeled using the time-domain impulse responses of the mixing filters. We propose a Student's t time-frequency source model based on non-negative matrix factorization (NMF). The Student's t distribution being heavy-tailed with respect to the Gaussian, it provides some flexibility in the modeling of the sources. We also study a simpler Student's t sparse source model within the same general source separation framework. The inference procedure relies on a variational expectation-maximization algorithm. Experiments show the advantage of using an NMF model compared with the sparse source model. While the Student's t NMF source model leads to slightly better results than our previous Gaussian one, we demonstrate the superiority of our method over two other approaches from the literature.
Fichier principal
Vignette du fichier
LeglaiveBadeauRichard_final.pdf (264.96 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01531243 , version 1 (29-06-2017)

Identifiants

  • HAL Id : hal-01531243 , version 1

Citer

Simon Leglaive, Roland Badeau, Gael Richard. Semi-Blind Student's t Source Separation for Multichannel Audio Convolutive Mixtures. 25th European Signal Processing Conference (EUSIPCO), Aug 2017, Kos, Greece. pp.2323-2327. ⟨hal-01531243⟩
121 Consultations
233 Téléchargements

Partager

Gmail Facebook X LinkedIn More