Learning to Play like the Great Pianists
Abstract
An application of relational instance-based learning to the complex task of expressive music performance is presented. We investigate to what extent a machine can automatically build ‘expressive profiles ’ of famous pianists using only minimal performance information extracted from audio CD recordings by pianists and the printed score of the played music. It turns out that the machine-generated expressive performances on unseen pieces are substantially closer to the real performances of the ‘trainer ’ pianist than those of all others. Two other interesting applications of the work are discussed: recognizing pianists from their style of playing, and automatic style replication.
Cite
Text
Tobudic and Widmer. "Learning to Play like the Great Pianists." International Joint Conference on Artificial Intelligence, 2005.Markdown
[Tobudic and Widmer. "Learning to Play like the Great Pianists." International Joint Conference on Artificial Intelligence, 2005.](https://mlanthology.org/ijcai/2005/tobudic2005ijcai-learning/)BibTeX
@inproceedings{tobudic2005ijcai-learning,
title = {{Learning to Play like the Great Pianists}},
author = {Tobudic, Asmir and Widmer, Gerhard},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2005},
pages = {871-876},
url = {https://mlanthology.org/ijcai/2005/tobudic2005ijcai-learning/}
}