A Bio-Inspired Music Genre Classification Framework using Modified AIS-Based Classifier
For decades now, scientific community are involved in various works to automate the human process of recognizing different types of music using different elements for example different instruments used. These efforts would imitate the human method of recognizing the music by considering every essent...
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| Format: | Article |
| Language: | en |
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The Society of Digital Information and Wireless Communications
2011
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| Online Access: | http://eprints.utem.edu.my/id/eprint/154/1/A_Bio-Inspired_Music_Genre_Classification_Framework_using_Modified_AIS-Based_Classifier.pdf http://eprints.utem.edu.my/id/eprint/154/ http://www.sdiwc.net/ijncaa |
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| _version_ | 1832715917330481152 |
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| author | Muda, N. A. Ahmad, S. Muda, A. K. |
| author_facet | Muda, N. A. Ahmad, S. Muda, A. K. |
| author_sort | Muda, N. A. |
| building | UTEM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknikal Malaysia Melaka |
| content_source | UTEM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | For decades now, scientific community are involved in various works to automate the human process of recognizing different types of music using different elements for example different instruments used. These efforts would imitate the human method of recognizing the music by considering every essential component of the songs from artist voice, melody of the music through to the type of instruments used. Various approaches or mechanisms are introduced and developed to automate the classification process since then. The results of these studies so far have been remarkable yet can still be improved. The aim of this research is to investigate Artificial Immune System (AIS) domain by focusing on the modified AIS-based classifier to solve this problem where the focuses are the censoring and monitoring modules. In this highlight, stages of music recognition are emphasized where feature extraction, feature selection, and feature classification processes are explained. Comparison of performances between proposed classifier and WEKA application is discussed. Almost 20 to 30 percent of classification accuracies are increased in this study. |
| format | Article |
| id | my.utem.eprints-154 |
| institution | Universiti Teknikal Malaysia Melaka |
| language | en |
| publishDate | 2011 |
| publisher | The Society of Digital Information and Wireless Communications |
| record_format | eprints |
| spelling | my.utem.eprints-1542021-09-21T15:25:01Z http://eprints.utem.edu.my/id/eprint/154/ A Bio-Inspired Music Genre Classification Framework using Modified AIS-Based Classifier Muda, N. A. Ahmad, S. Muda, A. K. QA76 Computer software For decades now, scientific community are involved in various works to automate the human process of recognizing different types of music using different elements for example different instruments used. These efforts would imitate the human method of recognizing the music by considering every essential component of the songs from artist voice, melody of the music through to the type of instruments used. Various approaches or mechanisms are introduced and developed to automate the classification process since then. The results of these studies so far have been remarkable yet can still be improved. The aim of this research is to investigate Artificial Immune System (AIS) domain by focusing on the modified AIS-based classifier to solve this problem where the focuses are the censoring and monitoring modules. In this highlight, stages of music recognition are emphasized where feature extraction, feature selection, and feature classification processes are explained. Comparison of performances between proposed classifier and WEKA application is discussed. Almost 20 to 30 percent of classification accuracies are increased in this study. The Society of Digital Information and Wireless Communications 2011 Article NonPeerReviewed text en http://eprints.utem.edu.my/id/eprint/154/1/A_Bio-Inspired_Music_Genre_Classification_Framework_using_Modified_AIS-Based_Classifier.pdf Muda, N. A. and Ahmad, S. and Muda, A. K. (2011) A Bio-Inspired Music Genre Classification Framework using Modified AIS-Based Classifier. International Journal of New Computer Architectures and their Applications (IJNCAA), 1 (2). pp. 304-315. ISSN 2220-9085 (online) http://www.sdiwc.net/ijncaa |
| spellingShingle | QA76 Computer software Muda, N. A. Ahmad, S. Muda, A. K. A Bio-Inspired Music Genre Classification Framework using Modified AIS-Based Classifier |
| title | A Bio-Inspired Music Genre Classification Framework using Modified AIS-Based Classifier |
| title_full | A Bio-Inspired Music Genre Classification Framework using Modified AIS-Based Classifier |
| title_fullStr | A Bio-Inspired Music Genre Classification Framework using Modified AIS-Based Classifier |
| title_full_unstemmed | A Bio-Inspired Music Genre Classification Framework using Modified AIS-Based Classifier |
| title_short | A Bio-Inspired Music Genre Classification Framework using Modified AIS-Based Classifier |
| title_sort | bio-inspired music genre classification framework using modified ais-based classifier |
| topic | QA76 Computer software |
| url | http://eprints.utem.edu.my/id/eprint/154/1/A_Bio-Inspired_Music_Genre_Classification_Framework_using_Modified_AIS-Based_Classifier.pdf http://eprints.utem.edu.my/id/eprint/154/ http://www.sdiwc.net/ijncaa |
| url_provider | http://eprints.utem.edu.my/ |