PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Genre classification of music by tonal harmony
Carlos Pérez-Sancho, David Rizo, Stefan Kersten and Rafael Ramirez
In: International Workshop on Machine Learning and Music, MML 2008, 5-12 Jul 2008, Helsinki, Finland.


We present a genre classification framework for audio music based on a symbolic classification system. Audio signals are transformed to a symbolic representation of harmony using a chord transcription algorithm, by computing Harmonic Pitch Class Profiles. Then, language models built from a groundtruth 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.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Information Retrieval & Textual Information Access
ID Code:5171
Deposited By:Carlos Pérez-Sancho
Deposited On:24 March 2009