MOTION INFORMED AUDIO SOURCE SEPARATION

In this paper we tackle the problem of single channel audio source separation driven by descriptors of the sounding object's motion. As opposed to previous approach es, motion is included as a soft-coupling constraint within the non negative matrix factorization framework. The proposed method is applied to a multi modal dataset of instruments in string quartet performance recordings where bow motion information is used for separation of string instruments. We show that the approach offers better source separation result than an audio-based baseline and the state-of-the-art multimodal-based approaches on these very challenging music mixtures.