Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Underdetermined Blind Audio Source Separation Using Modal Decomposition | Hindawi Publishing Corporation EURASIP Journal on Audio Speech and Music Processing Volume 2007 Article ID 85438 15 pages doi 2007 85438 Research Article Underdetermined Blind Audio Source Separation Using Modal Decomposition Abdeldjalil Aissa-El-Bey Karim Abed-Meraim and Yves Grenier Department TSI Ecole Nationale Superieure des Telecommunications ENST 46 Rue Barrault 75634 Paris Cedex 13 France Received 1 July 2006 Revised 20 November 2006 Accepted 14 December 2006 Recommended by Patrick A. Naylor 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. Copyright 2007 Abdeldjalil Aissa-El-Bey et al. 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. 1. INTRODUCTION The problem of blind source separation BSS consists of finding independent source signals from their observed mixtures without a priori knowledge on the actual mixing channels. The source separation problem is of interest in various applications 1 2 such as the localization and .
