An exploration of genetic algorithms for efficient musical instrument identification
An exploration of genetic algorithms for efficient musical instrument identification
- Author(s): R. Loughran ; J. Walker ; M. O'Neill
- DOI: 10.1049/cp.2009.1705
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- Author(s): R. Loughran ; J. Walker ; M. O'Neill Source: IET Irish Signals and Systems Conference (ISSC 2009), 2009 page ()
- Conference: IET Irish Signals and Systems Conference (ISSC 2009)
- DOI: 10.1049/cp.2009.1705
- ISBN: 978 1 84919 213 2
- Location: Dublin, Ireland
- Conference date: 10-11 June 2009
- Format: PDF
This study explores the use of genetic algorithms (GA) in optimising feature selection for musical instrument recognition. 95 timbral features were used to classify 3006 musical instrument samples into 5 instrument groups. A GA was used to optimise the best selection of features to use with an multi-layered perceptron (MLP) to classify the instruments. Of all the features examined, the Centroid Evolution was found to be the most important. The system was run a number of times with varying numbers of features as determined by the GA. The accuracy of the classifier was not reduced with a reduction in features, indicating that the GA successfully determined the best features to use. (6 pages)
Inspec keywords: acoustic signal processing; musical instruments; genetic algorithms; feature extraction; multilayer perceptrons; musical acoustics
Subjects: Acoustic signal processing; Audio equipment and systems; Optimisation techniques; Neural computing techniques; Music and musical instruments; Signal processing and detection; Digital signal processing
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