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On the Use of Anti-Word Models for Audio Music Annotation and Retrieval

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2 Author(s)
Zhi-Sheng Chen ; Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu, Taiwan ; Jang, J.-S.R.

Query-by-semantic-description (QBSD) is a natural way for searching/annotating music in a large database. To improve QBSD, we propose the use of anti-words for each annotation word based on the concept of supervised multiclass labeling (SML). More specifically, words that are highly associated with the opposite semantic meaning of a word constitute its anti-word set. By modeling both a word and its anti-word set, our annotation system can achieve 31.1% of equal mean per-word precision and recall, while the original SML model achieves 27.8%. Moreover, by constructing the models of the anti-word explicitly, the performance is also significantly improved for the retrieval system, especially when the query keyword is the antonym of an existing annotation word.

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Audio, Speech, and Language Processing, IEEE Transactions on  (Volume:17 ,  Issue: 8 )