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Z. Chen, J. Zen, and JY. RO. Jang, "Music Annotation and Retrieval System Using Anti-Models," Paper 7540, (2008 October.). doi: Z. Chen, J. Zen, and JY. RO. Jang, "Music Annotation and Retrieval System Using Anti-Models," Paper 7540, (2008 October.). doi:
Abstract: Query-by-semantic-description (QBSD) is a natural way for searching/annotating music in a large database. We propose such a system by considering anti-words for each annotation word based on the concept of supervised multi-class labeling (SML). Moreover, words that are highly correlated with the anti-semantic meaning of a word constitute its anti-word set. By modeling both a word and its anti-word set, our system can achieve +8.21% and +1.6% gains of average precision and recall against SML under the condition of an equal average number of annotation words, that is, 10. By incorporating anti-models, we also allow queries with anti-semantic words, which is not an option for previous systems.

@article{chen2008music,
author={chen, zhi-sheng and zen, jia-min and jang, jyh-shing roger},
journal={journal of the audio engineering society},
title={music annotation and retrieval system using anti-models},
year={2008},
volume={},
number={},
pages={},
doi={},
month={october},} @article{chen2008music,
author={chen, zhi-sheng and zen, jia-min and jang, jyh-shing roger},
journal={journal of the audio engineering society},
title={music annotation and retrieval system using anti-models},
year={2008},
volume={},
number={},
pages={},
doi={},
month={october},
abstract={query-by-semantic-description (qbsd) is a natural way for searching/annotating music in a large database. we propose such a system by considering anti-words for each annotation word based on the concept of supervised multi-class labeling (sml). moreover, words that are highly correlated with the anti-semantic meaning of a word constitute its anti-word set. by modeling both a word and its anti-word set, our system can achieve +8.21% and +1.6% gains of average precision and recall against sml under the condition of an equal average number of annotation words, that is, 10. by incorporating anti-models, we also allow queries with anti-semantic words, which is not an option for previous systems.},}

TY - paper
TI - Music Annotation and Retrieval System Using Anti-Models
SP - EP -
AU - Chen, Zhi-Sheng
AU - Zen, Jia-Min
AU - Jang, Jyh-Shing Roger
PY - 2008
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - October 2008 TY - paper
TI - Music Annotation and Retrieval System Using Anti-Models
SP - EP -
AU - Chen, Zhi-Sheng
AU - Zen, Jia-Min
AU - Jang, Jyh-Shing Roger
PY - 2008
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - October 2008
AB - Query-by-semantic-description (QBSD) is a natural way for searching/annotating music in a large database. We propose such a system by considering anti-words for each annotation word based on the concept of supervised multi-class labeling (SML). Moreover, words that are highly correlated with the anti-semantic meaning of a word constitute its anti-word set. By modeling both a word and its anti-word set, our system can achieve +8.21% and +1.6% gains of average precision and recall against SML under the condition of an equal average number of annotation words, that is, 10. By incorporating anti-models, we also allow queries with anti-semantic words, which is not an option for previous systems.