Music Style Mining and Classification by Melody
Summary :
Music style is one of the features that people used to classify music. Discovery of music style is helpful for the design of content-based music retrieval systems. In this paper we investigated the mining and classification of music style by melody from a collection of MIDI music. We extracted the chord from the melody and investigated the representation of extracted features and corresponding mining techniques for music classification. Experimental results show that the classification achieved 64% to 84% accuracy for two-way classification.
- Publication
- IEICE TRANSACTIONS on Information Vol.E86-D No.3 pp.655-659
- Publication Date
- 2003/03/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- LETTER
- Category
- Speech and Hearing
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Man-Kwan SHAN, Fang-Fei KUO, "Music Style Mining and Classification by Melody" in IEICE TRANSACTIONS on Information,
vol. E86-D, no. 3, pp. 655-659, March 2003, doi: .
Abstract: Music style is one of the features that people used to classify music. Discovery of music style is helpful for the design of content-based music retrieval systems. In this paper we investigated the mining and classification of music style by melody from a collection of MIDI music. We extracted the chord from the melody and investigated the representation of extracted features and corresponding mining techniques for music classification. Experimental results show that the classification achieved 64% to 84% accuracy for two-way classification.
URL: https://global.ieice.org/en_transactions/information/10.1587/e86-d_3_655/_p
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@ARTICLE{e86-d_3_655,
author={Man-Kwan SHAN, Fang-Fei KUO, },
journal={IEICE TRANSACTIONS on Information},
title={Music Style Mining and Classification by Melody},
year={2003},
volume={E86-D},
number={3},
pages={655-659},
abstract={Music style is one of the features that people used to classify music. Discovery of music style is helpful for the design of content-based music retrieval systems. In this paper we investigated the mining and classification of music style by melody from a collection of MIDI music. We extracted the chord from the melody and investigated the representation of extracted features and corresponding mining techniques for music classification. Experimental results show that the classification achieved 64% to 84% accuracy for two-way classification.},
keywords={},
doi={},
ISSN={},
month={March},}
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TY - JOUR
TI - Music Style Mining and Classification by Melody
T2 - IEICE TRANSACTIONS on Information
SP - 655
EP - 659
AU - Man-Kwan SHAN
AU - Fang-Fei KUO
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E86-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2003
AB - Music style is one of the features that people used to classify music. Discovery of music style is helpful for the design of content-based music retrieval systems. In this paper we investigated the mining and classification of music style by melody from a collection of MIDI music. We extracted the chord from the melody and investigated the representation of extracted features and corresponding mining techniques for music classification. Experimental results show that the classification achieved 64% to 84% accuracy for two-way classification.
ER -
English
