@INPROCEEDINGS{Karydis2006,
  AUTHOR =       {Ioannis Karydis},
  TITLE =        {Symbolic Music Genre Classification based on Note Pitch and Duration},
  BOOKTITLE =    {Advances in Databases and Information Systems},
  YEAR =         {2006},
  pages =        {329--338},
  abstract =     {This paper presents a music genre classification system that relies on note pitch and duration features, derived from their respective histograms. Feature histograms provide a simple but yet effective classifier for the purposes of genre classification in intra-classical genres such as sonatas, fugues, mazurkas, etc. Detailed experimental results illustrate the significant performance gains due to the proposed features, compared to existing baseline features.},
  keywords =     {Music genre classification, music features, histograms, pitch, duration, content-based information retrieval},
  note =         {Best student paper award},
}