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The ideal data representation for feature extraction of traditional Malay musical instrument sounds classification

Senan, Norhalina and Ibrahim, Rosziati and Mohd Nawi, Nazri and Mohd Mokji, Musa and Herawan, Tutut (2010) The ideal data representation for feature extraction of traditional Malay musical instrument sounds classification. In: ICIC'10 Proceedings of the 6th International Conference on Advanced Intelligent Computing Theories and Applications: Intelligent Computing, 18-21 August 2010, Changsha, China.

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Abstract

In presenting the appropriate data sets, various data representation and feature extraction methods have been discovered previously. However, almost all the existing methods are utilized based on the Western musical instruments. In this study, the data representation and feature extraction methods are applied towards Traditional Malay musical instruments sounds classification. The impact of five factors that might affecting the classification accuracy which are the audio length, segmented frame size, starting point, data distribution and data fraction (for training and testing) are investigated. The perception-based and MFCC features schemes with total of 37 features was used. While, Multi-Layered Perceptrons classifier is employed to evaluate the modified data sets in terms of the classification performance. The results show that the highest accuracy of 97.37% was obtained from the best data sets with the combination of full features.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: data representation; feature extraction; multi-layered perceptrons; traditional malay musical instruments
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Information Security
Depositing User: Normajihan Abd. Rahman
Date Deposited: 11 Apr 2013 02:14
Last Modified: 11 Apr 2013 02:14
URI: http://eprints.uthm.edu.my/id/eprint/3563
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