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 the 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 fiarly robust method for discovery and extraction of auditory objects from scenes.