Multi-modal feature integration for story boundary detection in broadcast news

Mi Mi Lu, Lei Xie, Zhong Hua Fu, Dong Mei Jiang, Yan Ning Zhang

科研成果: 书/报告/会议事项章节会议稿件同行评审

10 引用 (Scopus)

摘要

This paper investigates how to integrate multi-modal features for story boundary detection in broadcast news. The detection problem is formulated as a classification task, i.e., classifying each candidate into boundary/non-boundary based on a set of features. We use a diverse collection of features from text, audio and video modalities: lexical features capturing the semantic shifts of news topics and audio/video features reflecting the editorial rules of broadcast news. We perform a comprehensive evaluation on boundary detection performance for six popular classifiers, including decision tree (DT), Bayesian network (BN), naive Bayesian (NB) classifier, multi-layer peceptron (MLP), support vector machines (SVM) and maximum entropy (ME) classifier. Results show that BN and DT can generally achieve superior performances over other classifiers and BN offers the best F1-measure. Analysis of BN and DT reveals important inter-feature dependencies and complementarities that contribute significantly to the performance gain.

源语言英语
主期刊名2010 7th International Symposium on Chinese Spoken Language Processing, ISCSLP 2010 - Proceedings
420-425
页数6
DOI
出版状态已出版 - 2010
活动2010 7th International Symposium on Chinese Spoken Language Processing, ISCSLP 2010 - Tainan, 中国台湾
期限: 29 11月 20103 12月 2010

出版系列

姓名2010 7th International Symposium on Chinese Spoken Language Processing, ISCSLP 2010 - Proceedings

会议

会议2010 7th International Symposium on Chinese Spoken Language Processing, ISCSLP 2010
国家/地区中国台湾
Tainan
时期29/11/103/12/10

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