+ General Information
+ Members
+ Research
+ Intranet

PRAIg '16 / +pics


AERFAI Summer School on Deep Learning


Alicante July 5-6, 2017

10th international workshop on Machine Learning and Music


Barcelona: 16th October 2017



  1. Pérez-Sancho, C.; Rizo, D.; Iñesta, J.M.; Ponce de León, P.J.; Kersten, S.; Ramirez, R.
    "Genre classification of music by tonal harmony"
    Intelligent Data Analysis, vol. 14, pp. 533-545 (2010)
    : bibtex

    In this paper we present a genre classification framework for audio music based on a symbolic classification system. Audio signals are transformed into a symbolic representation of harmony using a chord transcription algorithm, based on the computation of harmonic pitch class profiles. Then, language models built from a ground truth of chord progressions for each genre are used to perform classification. We show that chord progressions are a suitable feature to represent musical genre, as they capture the harmonic rules relevant in each musical period or style. Finally, results using both pure symbolic information and chords transcribed from audio-from-MIDI are compared, in order to evaluate the effects of the transcription process in this task.

@article {
 author = "Pérez-Sancho, C.; Rizo, D.; Iñesta, J.M.; Ponce de León, P.J.; Kersten, S.; Ramirez, R.",
 title  = "Genre classification of music by tonal harmony",
 issn = "1088-467X",
 journal = "Intelligent Data Analysis",
 month = "September",
 number = "5",
 pages = "533-545",
 volume = "14",
 year = "2010"
Valid XHTML 1.0!Valid CSS!