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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chien-Hung Liu Chuan-Kang Ting |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Comput. Sci. & Inf. Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan (Chien-Hung Liu; Chuan-Kang Ting) |
| Abstract | Artificial intelligence (AI) has bloomed in many novel fields such as computational creativity. Recently, research on automatic composition using AI technology, especially evolutionary algorithms, has received considerable promising results. Traditionally, chromosomes are represented as a series of numbers to indicate the notes for evolutionary composition. This study attempts to explore the composition styles by mining music patterns of a specific composer. The patterns are used as genes for chromosome representation. Accordingly, the composition styles are considered in generating music by evolutionary algorithms. The fitness function is based on music theory to smooth the progression between phrases. Experimental results show that the patterns mined from compositions can reflect the composer's style and benefit generating satisfactory songs by evolutionary algorithms. |
| Starting Page | 2145 |
| Ending Page | 2152 |
| File Size | 475655 |
| Page Count | 8 |
| File Format | |
| e-ISBN | 9781479974924 |
| DOI | 10.1109/CEC.2015.7257149 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-25 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Data mining Biological cells Genetic algorithms Genetics Music Evolutionary computation Sociology creative intelligence evolutionary computation genetic algorithm pattern mining automatic composition |
| Content Type | Text |
| Resource Type | Article |
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