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:	Harya, Wicaksana, Septian, Hartono, Foo, Say Wei
Other Authors:	School of Electrical and Electronic Engineering
Format:	Conference or Workshop Item
Language:	English
Published:	2009
Online Access:	https://hdl.handle.net/10356/90832 http://hdl.handle.net/10220/4671
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-90832
record_format	dspace
spelling	sg-ntu-dr.10356-908322020-03-07T13:24:46Z Recognition of musical instruments Harya, Wicaksana Septian, Hartono Foo, Say Wei School of Electrical and Electronic Engineering IEEE Asia Pacific Conference on Circuits and Systems (2006 : Singapore) 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. Published version 2009-06-24T00:57:26Z 2019-12-06T17:54:51Z 2009-06-24T00:57:26Z 2019-12-06T17:54:51Z 2006 2006 Conference Paper Harya, W., Septian, H., & Foo, S. W. (2006). Recognition of musical instruments. In Proceedings of the IEEE Asia Pacific Conference on Circuits and Systems 2006: (pp.327-330). Nanyang Technological University, Singapore. https://hdl.handle.net/10356/90832 http://hdl.handle.net/10220/4671 10.1109/APCCAS.2006.342417 en ©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. http://www.ieee.org/portal/site. 4 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
country	Singapore
collection	DR-NTU
language	English
description	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.
author2	School of Electrical and Electronic Engineering
author_facet	School of Electrical and Electronic Engineering Harya, Wicaksana Septian, Hartono Foo, Say Wei
format	Conference or Workshop Item
author	Harya, Wicaksana Septian, Hartono Foo, Say Wei
spellingShingle	Harya, Wicaksana Septian, Hartono Foo, Say Wei Recognition of musical instruments
author_sort	Harya, Wicaksana
title	Recognition of musical instruments
title_short	Recognition of musical instruments
title_full	Recognition of musical instruments
title_fullStr	Recognition of musical instruments
title_full_unstemmed	Recognition of musical instruments
title_sort	recognition of musical instruments
publishDate	2009
url	https://hdl.handle.net/10356/90832 http://hdl.handle.net/10220/4671
_version_	1681044136684158976

Recognition of musical instruments

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