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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fukumoto, M. |
| Copyright Year | 2014 |
| Description | Author affiliation: Comput. Sci. & Eng., Fukuoka Inst. of Technol., Fukuoka, Japan (Fukumoto, M.) |
| Abstract | Music chord progression is one of musical elements that compose music piece. The music chord progression can be created freely by a user, however, combination of music chords is innumerable to define the progression. To resolve this problem, chord progression theory and basic patterns are often used. However, with these methods, it is hard for general users to create a music progression suited for each user's feelings. In order to create the chord progression suited for the user's feelings, user's own basic music knowledge and experience are required. In our previous study, we have proposed Interactive Genetic Algorithm (IGA) that creates music chord progression. In the IGA, Genetic Algorithm was used as evolutionary algorithm. In this study, through two listening experiments, we investigated the efficacy of the proposed IGA creating music chord progression. As the experiments, searching and evaluating experiments were conducted. As targets of creation of the chord progression, "bright" and "dark" chord progressions were selected as experimental conditions. In the result of the searching experiment, significant increases of fitness value were observed in both of the conditions. In the results of the evaluating experiment, in the 13th generation, large difference in impression between the conditions was observed. |
| Starting Page | 757 |
| Ending Page | 762 |
| File Size | 423515 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479941742 |
| e-ISBN | 9781479941735 |
| DOI | 10.1109/IIAI-AAI.2014.153 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-08-31 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | User's Feelings Music Chord Progression Sociology Music IEC Interactive Genetic Algorithm Evolutionary computation Evolutionary Computation Music Composition Statistics Optimization Genetic algorithms |
| Content Type | Text |
| Resource Type | Article |
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