| Project/Area Number |
10680373
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
NUMAO Masayuki Tokyo Institute of Technology, Graduate School of Information Science and Engineering, Associate professor, 大学院・情報理工学研究科, 助教授 (30198551)
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| Co-Investigator(Kenkyū-buntansha) |
村田 剛志 群馬大学, 工学部, 助手 (90242289)
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| Project Period (FY) |
1998 – 2000
|
| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥3,000,000 (Direct Cost: ¥3,000,000)
Fiscal Year 2000: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1999: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 1998: ¥1,600,000 (Direct Cost: ¥1,600,000)
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| Keywords | Machine Learning / Computer Music / Multimedia Authoring / Multistrategy Learning / Automatic Arrangement / Kansei Information / Karaoke / Authoring Support |
|---|
| Research Abstract |
We propose a method to locate relations and constraints between a music score and its impressions, by which we show that machine learning techniques may provide a powerful tool for composing music and analyzing human feelings. We examine its generality by modifying some arrangements to provide the subjects with a speci-fied impression. This research introduces some user interfaces. They are capable of predicting feelings and creating new objects based on seed structures, such as spec-trums and their transition for sounds that have been extracted and are perceived as favorable by the test subject.
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