IEICE TRANSACTIONS on Information
An Informative Feature Selection Method for Music Genre Classification
Summary :
This letter presents a new automatic musical genre classification method based on an informative song-level representation, in which the mutual information between the feature and the genre label is maximized. By efficiently combining distance-based indexing with informative features, the proposed method represents a song as one vector instead of complex statistical models. Experiments on an audio genre DB show that the proposed method can achieve the classification accuracy comparable or superior to the state-of-the-art results.
- Publication
- IEICE TRANSACTIONS on Information Vol.E94-D No.6 pp.1362-1365
- Publication Date
- 2011/06/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E94.D.1362
- Type of Manuscript
- LETTER
- Category
- Music Information Processing
Authors
Keyword
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Jin Soo SEO, "An Informative Feature Selection Method for Music Genre Classification" in IEICE TRANSACTIONS on Information,
vol. E94-D, no. 6, pp. 1362-1365, June 2011, doi: 10.1587/transinf.E94.D.1362.
Abstract: This letter presents a new automatic musical genre classification method based on an informative song-level representation, in which the mutual information between the feature and the genre label is maximized. By efficiently combining distance-based indexing with informative features, the proposed method represents a song as one vector instead of complex statistical models. Experiments on an audio genre DB show that the proposed method can achieve the classification accuracy comparable or superior to the state-of-the-art results.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E94.D.1362/_p
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@ARTICLE{e94-d_6_1362,
author={Jin Soo SEO, },
journal={IEICE TRANSACTIONS on Information},
title={An Informative Feature Selection Method for Music Genre Classification},
year={2011},
volume={E94-D},
number={6},
pages={1362-1365},
abstract={This letter presents a new automatic musical genre classification method based on an informative song-level representation, in which the mutual information between the feature and the genre label is maximized. By efficiently combining distance-based indexing with informative features, the proposed method represents a song as one vector instead of complex statistical models. Experiments on an audio genre DB show that the proposed method can achieve the classification accuracy comparable or superior to the state-of-the-art results.},
keywords={},
doi={10.1587/transinf.E94.D.1362},
ISSN={1745-1361},
month={June},}
Copy
TY - JOUR
TI - An Informative Feature Selection Method for Music Genre Classification
T2 - IEICE TRANSACTIONS on Information
SP - 1362
EP - 1365
AU - Jin Soo SEO
PY - 2011
DO - 10.1587/transinf.E94.D.1362
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E94-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2011
AB - This letter presents a new automatic musical genre classification method based on an informative song-level representation, in which the mutual information between the feature and the genre label is maximized. By efficiently combining distance-based indexing with informative features, the proposed method represents a song as one vector instead of complex statistical models. Experiments on an audio genre DB show that the proposed method can achieve the classification accuracy comparable or superior to the state-of-the-art results.
ER -
English
