AUDIO SOURCE SEPARATION INFORMED BY REDUNDANCY WITH GREEDY MULTISCALE DECOMPOSITIONS

Manuel Moussallam (1) , Gael Richard (2, 3) , Laurent Daudet (4)

1 LTCI - Laboratoire Traitement et Communication de l'Information
2 S2A - Signal, Statistique et Apprentissage
3 TSI - Département Traitement du Signal et des Images
4 ESPCI Paris - Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris

This paper describes a greedy algorithm for audio source separation of repeated musical patterns. The problem is understood as retrieving from a set of mixtures the part that is redundant among them and the parts that are specific to only one mixture. The key assumption is the sparsity of all the sources in the same multiscale dictionary. Synthetic and real life examples of source separation of hand cut repeated musical patterns are exposed. Results shows that the proposed method succeeds in simultaneously providing a sparse approximant of the mixtures and a separation of the sources.

Keywords: Simultaneous sparse approximation; audio source separation; greedy decompositions

Domains: Computer Science [cs]; Data Structures and Algorithms [cs.DS]; Computer Science [cs]; Signal and Image Processing; Computer Science [cs]; Sound [cs.SD]

Manuel Moussallam, Gael Richard, Laurent Daudet. AUDIO SOURCE SEPARATION INFORMED BY REDUNDANCY WITH GREEDY MULTISCALE DECOMPOSITIONS. European Signal Processing Conference, Aug 2012, Bucarest, Romania. pp.2644-2648. ⟨hal-00735234⟩