Towards music fitness evaluation with the hierarchical SOM
In any evolutionary search system, the fitness raters are most crucial in determining successful evolution. In this paper, we propose a Hierarchical Self Organizing Map based sequence predictor as a fitness evaluator for a music evolution system. The hierarchical organization of information in the H...
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| Format: | Article |
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SPRINGER-VERLAG BERLIN
2008
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| Online Access: | http://shdl.mmu.edu.my/2792/ |
| _version_ | 1848790151302479872 |
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| author | Edwin Hui Hean, Law Somnuk, Phon-Amnuaisuk |
| author_facet | Edwin Hui Hean, Law Somnuk, Phon-Amnuaisuk |
| author_sort | Edwin Hui Hean, Law |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | In any evolutionary search system, the fitness raters are most crucial in determining successful evolution. In this paper, we propose a Hierarchical Self Organizing Map based sequence predictor as a fitness evaluator for a music evolution system. The hierarchical organization of information in the HSOM allows prediction to be performed with multiple levels of contextual information. Here, we detail the design and implementation of such a HSOM system. From the experimental setup, we show that the HSOM's prediction performance exceeds that of a Markov prediction system when using randomly generated and musical phrases. |
| first_indexed | 2025-11-14T18:08:03Z |
| format | Article |
| id | mmu-2792 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:08:03Z |
| publishDate | 2008 |
| publisher | SPRINGER-VERLAG BERLIN |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-27922011-09-19T08:19:23Z http://shdl.mmu.edu.my/2792/ Towards music fitness evaluation with the hierarchical SOM Edwin Hui Hean, Law Somnuk, Phon-Amnuaisuk T Technology (General) QA75.5-76.95 Electronic computers. Computer science In any evolutionary search system, the fitness raters are most crucial in determining successful evolution. In this paper, we propose a Hierarchical Self Organizing Map based sequence predictor as a fitness evaluator for a music evolution system. The hierarchical organization of information in the HSOM allows prediction to be performed with multiple levels of contextual information. Here, we detail the design and implementation of such a HSOM system. From the experimental setup, we show that the HSOM's prediction performance exceeds that of a Markov prediction system when using randomly generated and musical phrases. SPRINGER-VERLAG BERLIN 2008 Article NonPeerReviewed Edwin Hui Hean, Law and Somnuk, Phon-Amnuaisuk (2008) Towards music fitness evaluation with the hierarchical SOM. SPRINGER-VERLAG BERLIN, 4974. pp. 443-452. http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=1&SID=Q1Mem7jkjbFNK9JeCJh&page=83&doc=829 |
| spellingShingle | T Technology (General) QA75.5-76.95 Electronic computers. Computer science Edwin Hui Hean, Law Somnuk, Phon-Amnuaisuk Towards music fitness evaluation with the hierarchical SOM |
| title | Towards music fitness evaluation with the hierarchical SOM |
| title_full | Towards music fitness evaluation with the hierarchical SOM |
| title_fullStr | Towards music fitness evaluation with the hierarchical SOM |
| title_full_unstemmed | Towards music fitness evaluation with the hierarchical SOM |
| title_short | Towards music fitness evaluation with the hierarchical SOM |
| title_sort | towards music fitness evaluation with the hierarchical som |
| topic | T Technology (General) QA75.5-76.95 Electronic computers. Computer science |
| url | http://shdl.mmu.edu.my/2792/ http://shdl.mmu.edu.my/2792/ |