|
Title:
|
Discovering Expressive Transformation Rules from Saxophone Jazz Performances
|
|
Author:
|
Ramírez, Rafael,1966-; Hazan, Amaury; Gómez Gutiérrez, Emilia, 1975-; Maestre Gómez, Esteban; Serra, Xavier
|
|
Abstract:
|
If-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. |
|
Abstract:
|
This work is supported by the Spanish TIC project
ProMusic (TIC 2003-07776-C02-01). |
|
Rights:
|
© Taylor & Francis. This is an electronic version of an article published in Ramirez R, Hazan A, Gómez E, Maestre E, Serra X. Discovering Expressive Transformation Rules from Saxophone Jazz Performances. Journal of New Music Research. 2005;34(4):319-30. Journal of New Music Research is available online at: https://www.tandfonline.com/doi/abs/10.1080/09298210600578097
|
|
Document type:
|
Article
Article - Accepted version |
|
Published by:
|
Taylor & Francis (Routledge)
|
|
Share:
|
|
