| Title | Genre Classification of Music by Tonal Harmony |
| Publication Type | Conference Paper |
| Year of Publication | 2008 |
| Conference Name | International Workshop on Machine Learning and Music, International Conference on Machine Learning |
| Authors | Perez-Sancho, C., Rizo D., Kersten S., & Ramirez R. |
| Abstract | 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.
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