Open Access

Underdetermined Blind Audio Source Separation Using Modal Decomposition

  • Abdeldjalil Aïssa-El-Bey1Email author,
  • Karim Abed-Meraim1 and
  • Yves Grenier1
EURASIP Journal on Audio, Speech, and Music Processing20072007:085438

https://doi.org/10.1155/2007/85438

Received: 1 July 2006

Accepted: 14 December 2006

Published: 13 March 2007

Abstract

This paper introduces new algorithms for the blind separation of audio sources using modal decomposition. Indeed, audio signals and, in particular, musical signals can be well approximated by a sum of damped sinusoidal (modal) components. Based on this representation, we propose a two-step approach consisting of a signal analysis (extraction of the modal components) followed by a signal synthesis (grouping of the components belonging to the same source) using vector clustering. For the signal analysis, two existing algorithms are considered and compared: namely the EMD (empirical mode decomposition) algorithm and a parametric estimation algorithm using ESPRIT technique. A major advantage of the proposed method resides in its validity for both instantaneous and convolutive mixtures and its ability to separate more sources than sensors. Simulation results are given to compare and assess the performance of the proposed algorithms.

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Authors’ Affiliations

(1)
Départment TSI, École Nationale Supérieure des Télécommunications (ENST)

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Copyright

© Abdeldjalil Aïssa-El-Bey et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.