The Bodhidharma System and the Results of the Mirex 2005 Symbolic Genre Classification Contest

This paper discusses the results of the MIREX 2005 symbolic genre classification contest and describes the Bodhidharma system, which attained the highest classification success rates in all four of the evaluated categories. Five systems were submitted to this contest, which was conducted independently at the University of Illinois at Urbana-Champagne (UIUC). Each system was evaluated in two different experiments, one involving thirty-eight genre classes and one involving nine classes. Success rates were measured in two ways: one based only on how well each system was able to find the single correct genre of each recording, and the other giving partial scores to incorrect classifications that were relatively close to the correct genre. Evaluations were performed using stratified cross-validation. Bodhidharma is a sophisticated system that utilizes a combination of flat, hierarchical and round-robin classification strategies based on classifier ensembles consisting of feedforward neural networks and k-nearest neighbour classifiers. Bodhidharma bases its classifications on 111 high-level features that it extracts from MIDI recordings. Each classifier ensemble uses genetic algorithms to evolve a weighted sub-set of the features that are appropriate for that particular ensemble.