Improving automatic music classification performance by extracting features from different types of data

@inproceedings{McKay2010ImprovingAM,
  title={Improving automatic music classification performance by extracting features from different types of data},
  author={Cory McKay and Ichiro Fujinaga},
  booktitle={Multimedia Information Retrieval},
  year={2010}
}
This paper discusses two sets of automatic musical genre classification experiments. Promising research directions are then proposed based on the results of these experiments. The first set of experiments was designed to examine the utility of combining features extracted from separate and independent audio, symbolic and cultural sources of musical information. The results from this set of experiments indicate that combining feature types can indeed substantively improve classification… CONTINUE READING

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