2000 Fiscal Year Final Research Report Summary
Supporting Multimedia Authoring by using Machine Learning
| Project/Area Number |
10680373
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Intelligent informatics
|
|---|
| Research Institution | Tokyo Institute of Technology |
|---|
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)
|
|---|
| Project Period (FY) |
1998 – 2000
|
| 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.
|
