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...

Full description

Bibliographic Details
Main Authors: Harya, Wicaksana, Septian, Hartono, Foo, Say Wei
Other Authors: School of Electrical and Electronic Engineering
Format: Conference Paper
Language:English
Published: 2009
Online Access:https://hdl.handle.net/10356/90832
http://hdl.handle.net/10220/4671
_version_ 1826125089971634176
author Harya, Wicaksana
Septian, Hartono
Foo, Say Wei
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Harya, Wicaksana
Septian, Hartono
Foo, Say Wei
author_sort Harya, Wicaksana
collection NTU
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.
first_indexed 2024-10-01T06:31:04Z
format Conference Paper
id ntu-10356/90832
institution Nanyang Technological University
language English
last_indexed 2024-10-01T06:31:04Z
publishDate 2009
record_format dspace
spelling ntu-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
spellingShingle Harya, Wicaksana
Septian, Hartono
Foo, Say Wei
Recognition of musical instruments
title Recognition of musical instruments
title_full Recognition of musical instruments
title_fullStr Recognition of musical instruments
title_full_unstemmed Recognition of musical instruments
title_short Recognition of musical instruments
title_sort recognition of musical instruments
url https://hdl.handle.net/10356/90832
http://hdl.handle.net/10220/4671
work_keys_str_mv AT haryawicaksana recognitionofmusicalinstruments
AT septianhartono recognitionofmusicalinstruments
AT foosaywei recognitionofmusicalinstruments