Underdetermined source separation with structured source priors - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2004

Underdetermined source separation with structured source priors


We consider the source extraction problem for stereo instantaneous musical mixtures with more than two sources. We prove that usual separation methods based only on spatial diversity have performance limitations when the sources overlap in the time-frequency plane. We propose a new separation scheme combining spatial diversity and structured source priors. We present possible priors based on nonlinear Independent Subspace Analysis (ISA) and Hidden Markov Models (HMM), whose parameters are learnt on solo musical excerpts. We show with an example that they actually improve the separation performance.
Fichier principal
Vignette du fichier
vincent_ICA04.pdf (353.85 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

inria-00544694 , version 1 (08-12-2010)


  • HAL Id : inria-00544694 , version 1


Emmanuel Vincent, Xavier Rodet. Underdetermined source separation with structured source priors. 5th Int. Conf. on Independent Component Analysis and Blind Signal Separation (ICA), Sep 2004, Granada, Spain. pp.327--332. ⟨inria-00544694⟩


49 View
226 Download


Gmail Facebook X LinkedIn More