1. Octavio Vicente and José M. Iñesta

, vol. Proceedings of the Int. Conf. on Pattern Recognition Applications and Methods (ICPRAM 2012), pp. 449--458. Vilamoura, Portugal (2012)

Standard MIDI files consist of a number of tracks containing information that can be considered as a symbolic representation of music. Usually each track represents an instrument or voice in a music piece. The goal for this work is to identify the track that contains the bass line. This information is very relevant for a number of tasks like rhythm analysis or harmonic segmentation, among others. It is not easy since a bass line can be performed by very different kinds of instruments. We have approached this problem by using statistical features from the symbolic representation of music and a random forest classifier. The first experiment was to classify a track as bass or non-bass. Then we have tried to select the correct bass track in a multi-track MIDI file. Eventually, we have studied the issue of how different sources of information can help in this latter task. In particular, we have analyzed the interactions between bass and melody information. Yielded results were very accurate and melody track identification was significantly improved when using this kind of multimodal help.