Automatic Genre Classification Using Large High-Level Musical Feature Sets

@inproceedings{McKay2004AutomaticGC,
  title={Automatic Genre Classification Using Large High-Level Musical Feature Sets},
  author={Cory McKay and Ichiro Fujinaga},
  booktitle={ISMIR},
  year={2004}
}
This paper presents a system that extracts 109 musical features from symbolic recordings (MIDI, in this case) and uses them to classify the recordings by genre. The features used here are based on instrumentation, texture, rhythm, dynamics, pitch statistics, melody and chords. The classification is performed hierarchically using different sets of features at different levels of the hierarchy. Which features are used at each level, and their relative weightings, are determined using genetic… CONTINUE READING
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