A study on feature selection and classification techniques for automatic genre classification of traditional Malay music
Machine learning techniques for automated musical genre classification is currently widely studied. With large collections of digital musical files, one approach to classification is to classify by musical genres such as pop, rock and classical in Western music. Beat, pitch and temporal related feat...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
ISMIR
2008
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| Online Access: | http://psasir.upm.edu.my/id/eprint/40721/ http://psasir.upm.edu.my/id/eprint/40721/1/40721.pdf |
| _version_ | 1848849506432450560 |
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| author | Doraisamy, Shyamala Golzari, Shahram Mohd. Norowi, Noris Sulaiman, Md. Nasir Udzir, Nur Izura |
| author_facet | Doraisamy, Shyamala Golzari, Shahram Mohd. Norowi, Noris Sulaiman, Md. Nasir Udzir, Nur Izura |
| author_sort | Doraisamy, Shyamala |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Machine learning techniques for automated musical genre classification is currently widely studied. With large collections of digital musical files, one approach to classification is to classify by musical genres such as pop, rock and classical in Western music. Beat, pitch and temporal related features are extracted from audio signals and various machine learning algorithms are applied for classification. Features that resulted in better classification accuracies for Traditional Malay Music (TMM), in comparison to western music, in a previous study were beat related features. However, only the J48 classifier was used and in this study we perform a more comprehensive investigation on improving the classification of TMM. In addition, feature selection was performed for dimensionality reduction. Classification accuracies using classifiers of varying paradigms on a dataset comprising ten TMM genres were obtained. Results identify potentially useful classifiers and show the impact of adding a feature selection phase for TMM genre classification. |
| first_indexed | 2025-11-15T09:51:29Z |
| format | Conference or Workshop Item |
| id | upm-40721 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T09:51:29Z |
| publishDate | 2008 |
| publisher | ISMIR |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-407212015-09-21T09:28:29Z http://psasir.upm.edu.my/id/eprint/40721/ A study on feature selection and classification techniques for automatic genre classification of traditional Malay music Doraisamy, Shyamala Golzari, Shahram Mohd. Norowi, Noris Sulaiman, Md. Nasir Udzir, Nur Izura Machine learning techniques for automated musical genre classification is currently widely studied. With large collections of digital musical files, one approach to classification is to classify by musical genres such as pop, rock and classical in Western music. Beat, pitch and temporal related features are extracted from audio signals and various machine learning algorithms are applied for classification. Features that resulted in better classification accuracies for Traditional Malay Music (TMM), in comparison to western music, in a previous study were beat related features. However, only the J48 classifier was used and in this study we perform a more comprehensive investigation on improving the classification of TMM. In addition, feature selection was performed for dimensionality reduction. Classification accuracies using classifiers of varying paradigms on a dataset comprising ten TMM genres were obtained. Results identify potentially useful classifiers and show the impact of adding a feature selection phase for TMM genre classification. ISMIR 2008 Conference or Workshop Item NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/40721/1/40721.pdf Doraisamy, Shyamala and Golzari, Shahram and Mohd. Norowi, Noris and Sulaiman, Md. Nasir and Udzir, Nur Izura (2008) A study on feature selection and classification techniques for automatic genre classification of traditional Malay music. In: 9th International Conference on Music Information Retrieval, ISMIR 2008, 14-18 Sep. 2008, Philadelphia, USA. (pp. 331-336). http://ismir2008.ismir.net/papers/ISMIR2008_256.pdf |
| spellingShingle | Doraisamy, Shyamala Golzari, Shahram Mohd. Norowi, Noris Sulaiman, Md. Nasir Udzir, Nur Izura A study on feature selection and classification techniques for automatic genre classification of traditional Malay music |
| title | A study on feature selection and classification techniques for automatic genre classification of traditional Malay music |
| title_full | A study on feature selection and classification techniques for automatic genre classification of traditional Malay music |
| title_fullStr | A study on feature selection and classification techniques for automatic genre classification of traditional Malay music |
| title_full_unstemmed | A study on feature selection and classification techniques for automatic genre classification of traditional Malay music |
| title_short | A study on feature selection and classification techniques for automatic genre classification of traditional Malay music |
| title_sort | study on feature selection and classification techniques for automatic genre classification of traditional malay music |
| url | http://psasir.upm.edu.my/id/eprint/40721/ http://psasir.upm.edu.my/id/eprint/40721/ http://psasir.upm.edu.my/id/eprint/40721/1/40721.pdf |