Discovering Expressive Transformation Rules from Saxophone Jazz Performances

TitleDiscovering Expressive Transformation Rules from Saxophone Jazz Performances
Publication TypeJournal Article
Year of Publication2005
AuthorsRamirez, R., Hazan A., Gómez E., Maestre E., & Serra X.
Journal TitleJournal of New Music Research
AbstractIf-then rules are one of the most expressive and intuitive knowledge representations and their application to represent musical knowledge raises particularly interesting questions. In this paper, we describe an approach to learning expressive performance rules from monophonic recordings of jazz standards by a skilled saxophonist. We have first developed a melodic transcription system which extracts a set of acoustic features from the recordings producing a melodic representation of the expressive performance played by the musician. We apply machine learning techniques, namely inductive logic programming, to this representation in order to induce first order logic rules of expressive music performance.
preprint/postprint document
Final publication