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A study of the automatic classification of musical instrument sounds is presented. For this purpose, a large database of musical instrument sounds was built, which consists of both solo and duet stereo recordings. The classification process of musical instrument sounds is done on the basis of some soft computing techniques, such as neural networks. The results of the classification are given as a percentage of musical instrument sounds properly recognized by the system. A discussion of the system`s efficiency and limitations is presented. Conclusions and remarks concerning further development of this study are also included.:
Author (s): Kostek, Bozena;
Czyzewski, Andrzej;
Affiliation:
Technical University of Gdansk, Poland
(See document for exact affiliation information.)
AES Convention: 108
Paper Number:5115
Publication Date:
2000-02-06
Session subject:
Musical Instrument Acoustics; Electronic Music Technology
DOI:
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Kostek, Bozena; Czyzewski, Andrzej; 2000; Automatic Classification of Musical Sounds [PDF]; Technical University of Gdansk, Poland; Paper 5115; Available from: https://aes.org/publications/elibrary-page/?id=9223
Kostek, Bozena; Czyzewski, Andrzej; Automatic Classification of Musical Sounds [PDF]; Technical University of Gdansk, Poland; Paper 5115; 2000 Available: https://aes.org/publications/elibrary-page/?id=9223
@inproceedings{Kostek2000automatic,
title={{Automatic Classification of Musical Sounds}},
author={Kostek, Bozena and Czyzewski, Andrzej},
year={2000},
month={feb},
booktitle={Journal of the Audio Engineering Society},
publisher={Paper 5115; AES Convention 108; February 2000},
number={5115},
organization={AES},
}
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