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.
Authors:
Chen, Zhi-Sheng; Zen, Jia-Min; Jang, Jyh-Shing Roger
Affiliation:
National Tsing Hua University
AES Convention:
125 (October 2008)
Paper Number:
7540
Publication Date:
October 1, 2008
Subject:
Audio Content Management
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