Automatic glossary extraction: beyond terminology identification
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
HLT '91 Proceedings of the workshop on Speech and Natural Language
Topic transition detection using hierarchical hidden Markov and semi-Markov models
Proceedings of the 13th annual ACM international conference on Multimedia
Creating MAGIC: system for generating learning object metadata for instructional content
Proceedings of the 13th annual ACM international conference on Multimedia
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
| Hi-index | 0.00 |
This paper presents our latest work on structuring instructional videos into units of atomic topical segment so as to facilitate topic-based video browsing and offer efficient video authoring. Specifically, we developed a comprehensive text analysis component to first extract informative text cues such as keyword synonym set and sentence boundary information, from a video's transcript. These text cues are then applied with various audiovisual cues such as silence/music break and speech similarity, to identify topical segments. Early experiments carried out on collections of real data from targeted user communities have yielded good results, and the user feedback on using the generated topical segment information is very encouraging.