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Audio-Visual Content Analysis Based Clustering for Unsupervised Debate Indexing  

Keum, Ji-Soo (경희대학교 컴퓨터공학과)
Lee, Hyon-Soo (경희대학교 컴퓨터공학과)
Publication Information
The Journal of the Acoustical Society of Korea / v.27, no.5, 2008 , pp. 244-251 More about this Journal
Abstract
In this research, we propose an unsupervised debate indexing method using audio and visual information. The proposed method combines clustering results of speech by BIC and visual by distance function. The combination of audio-visual information reduces the problem of individual use of speech and visual information. Also, an effective content based analysis is possible. We have performed various experiments to evaluate the proposed method according to use of audio-visual information for five types of debate data. From experimental results, we found that the effect of audio-visual integration outperforms individual use of speech and visual information for debate indexing.
Keywords
Audio-Visual Content Analysis; Unsupervised Debate Indexing; Speaker Indexing;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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