Blind separation of audio sources using modal decomposition

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 steps approach consisting of a signal analysis (extraction of the modal components) followed by a signal synthesis (pairing of the components belonging to the same source) using vector clustering. For the signal analysis, two 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 ability to separate more sources than sensors. Simulation results are given to compare and assess the performances of the proposed algorithms.