Feature selection for automatic classification of musical instrument sounds
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
Feature Selection for Unsupervised Learning
The Journal of Machine Learning Research
Toward Integrating Feature Selection Algorithms for Classification and Clustering
IEEE Transactions on Knowledge and Data Engineering
Learning musical instrument skills through interactive sonification
NIME '06 Proceedings of the 2006 conference on New interfaces for musical expression
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Musical instrument recognition by pairwise classification strategies
IEEE Transactions on Audio, Speech, and Language Processing
A Study on Feature Analysis for Musical Instrument Classification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In recent year, most studies concerned with the classification of musical instruments sounds focus on western musical instruments. With the enormous amount of instruments data and features schemes, adapting the existing techniques for classifying the traditional Malay musical instruments sounds might not be as easy due to the differences in the sounds samples used. Thus, the existing framework and techniques that have been proposed for automatic musical instruments sounds classification system will be reviewed and evaluated especially on their performance in achieving the highest accuracy rate. As a result, a new framework for Traditional Malay Musical Instruments Sounds Classification System and the classification accuracy achieved in the preliminary experiment are presented.