| Title: | OS13-9 The research about editing system of performance information for player piano. -Develop inference methods using machine learning - |
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| Publication: | ICAROB2023 |
| Volume: | 28 |
| Pages: | 333-336 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2023.OS13-9 |
| Author(s): | Takaaki Ueno, Sakmongkon Chumkamon, Eiji Hayashi |
| Publication Date: | February 9, 2023 |
| Keywords: | Neural Network, Machine Learning, Long Short-Term Memory, Recurrent Neural Network, Automatic Piano, Computer Music |
| Abstract: | In 1996, Professor Eiji Hayashi of this laboratory developed an automatic piano performance system that aims to reproduce performance skills equivalent to those of humans.¹ However, this system does not have a function to infer performance expressions such as the strength and weakness of notes, and is not capable of expressing emotions such as intonation for each phrase, as is done by actual human performers. Therefore, the goal of this research was to reproduce the performances of world-famous pianists under the objective of "pursuit of more human-like performance expression. In the future, when this research matures and the human expression of the piano is clarified mathematically, the data will be used to reproduce human performances, which will fulfill the original purpose of this research. In this paper, we attempted to reproduce "Prelude Op.4 No.10" composed by Fryderyk Franciszek Chopin, using the worldfamous pianist "Vladimir Davidovich Ashkenazy" as the research subject. |
| PDF File: | https://alife-robotics.co.jp/members2023/icarob/data/html/data/OS/OS13/OS13-9.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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