A Case Based Approach to Expressivity-Aware Tempo Transformation
Abstract
The research presented in this paper focuses on global tempo transformations of monophonic audio recordings of saxophone jazz performances. We are investigating the problem of how a performance played at a particular tempo can be rendered automatically at another tempo, while preserving naturally sounding expressivity. Or, differently stated, how does expressiveness change with global tempo. Changing the tempo of a given melody is a problem that cannot be reduced to just applying a uniform transformation to all the notes of a musical piece. The expressive resources for emphasizing the musical structure of the melody and the affective content differ depending on the performance tempo. We present a case-based reasoning system called TempoExpress for addressing this problem, and describe the experimental results obtained with our approach.
Cite
Text
Grachten et al. "A Case Based Approach to Expressivity-Aware Tempo Transformation." Machine Learning, 2006. doi:10.1007/S10994-006-9025-9Markdown
[Grachten et al. "A Case Based Approach to Expressivity-Aware Tempo Transformation." Machine Learning, 2006.](https://mlanthology.org/mlj/2006/grachten2006mlj-case/) doi:10.1007/S10994-006-9025-9BibTeX
@article{grachten2006mlj-case,
title = {{A Case Based Approach to Expressivity-Aware Tempo Transformation}},
author = {Grachten, Maarten and Arcos, Josep Lluís and de Mántaras, Ramón López},
journal = {Machine Learning},
year = {2006},
pages = {411-437},
doi = {10.1007/S10994-006-9025-9},
volume = {65},
url = {https://mlanthology.org/mlj/2006/grachten2006mlj-case/}
}