Recognition of musical instruments
In this paper an automated method to recognize the musical instruments playing the musical signals is presented. Various features of the musical instruments and musical signals are investigated. The features can broadly be grouped into three categories: temporal, spectral, and cepstral featur...
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| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2009
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| Online Access: | https://hdl.handle.net/10356/90832 http://hdl.handle.net/10220/4671 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | In this paper an automated method to recognize the musical instruments playing the musical signals is presented. Various features of the musical instruments and musical signals are investigated. The features can broadly be grouped into three
categories: temporal, spectral, and cepstral features. A composite neural network structure is proposed as the classifier. The
performance of the composite neural network using a set of carefully chosen features is compared with that of the traditional
neural network. Experimental results show that the accuracy achieved using composite structure (94%) is significantly higher
than that using the traditional structure (88%) when more than four musical instruments are to be distinguished. |
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