1. Ponce de León, P.J.; Rizo, D.; Ramirez, R.; Iñesta, J.M.

, vol. Proceedings of the 5th Sound and Music Computing Conference , pp. 15-23. (2008)

We present preliminary work on automatic human-readable melody characterization. In order to obtain such a characterization, we (1) extract a set of statistical descriptors from the tracks in a dataset of MIDI files, (2) apply a rule induction algorithm to obtain a set of (crisp) classification rules for melody track identification, and (3) automatically transform the crisp rules into fuzzy rules by applying a genetic algorithm to generate the membership functions for the rule attributes. Some results are presented and discussed.