2019年10月
Estimation of the Kansei Information obtained from Musical Scores via Machine Learning Algorithms
Proc. of the 10th IEEE International Conference on Awareness Science and Technology (iCAST 2019)
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- 開始ページ
- 288
- 終了ページ
- 292
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- 出版者・発行元
- IEEE
This study investigates whether machine learning algorithms can be used to accurately classify tempo into two classes based only on the musical note sequence written on musical scores. Herein, the tempo that is manually estimated by looking at the score is simulated via Kansei (emotional) information processing. The tempo threshold was set at d = 120. Results showed that even after successful learning, the algorithms showed low recognition rates while classifying slow tempo class from the evaluation data and some data were erroneously recognized. In contrast, the algorithms showed high recognition rates when classifying fast tempo class from the evaluation data. The algorithms did not show any recognition error in the data.
- リンク情報
- ID情報
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- ISSN : 2325-5986
- Web of Science ID : WOS:000521753600051