Abstract

Abstract We present a novel method for discovering auditory objects from scenes in a self-organized manner. Our approach is using non-negativity constraints to find the building elements of a monaural auditory input. Surprisingly, although devoid of any statistical measures, this approach discovers independent elements in the scene similarly to previously reported methods employing ICA algorithms. The use of non-negativity constraints makes this work best suited for spectral magnitude analysis and provides a fairly robust method for discovery and extraction of auditory objects from scenes.