Convolutive common audio signal extraction

This paper addresses the extraction of a common signal among several mono audio tracks when this common signal undergoes a track-specific filtering. This problem arises in the extraction of a common music and effects track from a set of soundtracks in different languages. To this aim, a novel approach is proposed. The method is based on the dictionary modeling of track-specific and common signals, and is compared to a previous one proposed by the authors based on geometric considerations. The approach is integrated into a Non-Negative Matrix Factorization framework using the Itakura-Saito divergence. The method is evaluated on a synthetic database composed of filtered music and effects tracks, the filters being track-specific, and track-specific dialogs. The results show that this task becomes tractable, while the previously introduced method could not handle track-specific filtering.