NDLI: Semantic Analysis for Topical Segmentation of Videos

Content Provider	IEEE Xplore Digital Library
Author	Youngja Park Ying Li
Copyright Year	2007
Description	Author affiliation: IBM, Rochester (Youngja Park; Ying Li)
Abstract	Topic segmentation of videos enables topic-based categorization, retrieval and browsing and also facilitates efficient video authoring. Existing video topic segmentation techniques, however, are domain specific to news or narrative videos while generic approaches based on video shot analysis generate too fine-grained micro-segments. This paper addresses this challenge through a multi-modal semantic analysis technique for recognizing topical segments. We analyze the content of a video by using textual and audio features such as keyword synonym sets, sentence boundary information, silence/music breaks and speech similarity. Specifically, we propose a new natural language processing (NLP) technique for constructing synonym sets from video transcripts. A synonym set is a list of domain- specific keywords that are semantically related and represent a topic. We align the synonym sets with audio cues to identify the topical segments. Our experiments with six instructional videos show that the system produced very small number of false positives, and the topical segments generated by our system are 5.5 times longer on average compared to those generated by a state-of-the-art micro-segmentation system. The system has been embedded in an e-Learning project, and the user feedback on using the generated topical segments is very encouraging. The experiments were conducted with instructional videos, but our approach is domain-general and is not restricted to instructional videos.
Starting Page	161
Ending Page	168
File Size	323462
Page Count	8
File Format	PDF
ISBN	9780769529974
DOI	10.1109/ICSC.2007.31
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Couplings Speech analysis Gunshot detection systems Electronic learning Feedback Hidden Markov models Natural language processing Data mining Videos Information analysis
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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