Genre classification of music by tonal harmony
| Autor: | Stefan Kersten, Rafael Ramirez, Carlos Pérez-Sancho, José M. Iñesta, David Rizo, Pedro J. Ponce de León |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Ground truth
Audio signal InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g. HCI) business.industry Transcription (music) Computation Speech recognition Musical computer.software_genre Theoretical Computer Science Pitch class ComputingMethodologies_PATTERNRECOGNITION Artificial Intelligence Chord (music) Computer Vision and Pattern Recognition Artificial intelligence Language model business computer Natural language processing Mathematics |
| Zdroj: | Intelligent Data Analysis. 14:533-545 |
| ISSN: | 1571-4128 1088-467X |
| DOI: | 10.3233/ida-2010-0437 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|