File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Segmentation of lecture videos based on text: A method combining multiple linguistic features

TitleSegmentation of lecture videos based on text: A method combining multiple linguistic features
Authors
KeywordsComputers
Computer systems
Issue Date2004
PublisherI E E E, Computer Society. The Journal's web site is located at http://csdl2.computer.org/persagen/DLPublication.jsp?pubtype=p&acronym=HICSS
Citation
The 37th Annual Hawaii International Conference on System Sciences Proceedings, Hawaii, 5-8 January 2004 How to Cite?
AbstractIn multimedia-based e-Learning systems, there are strong needs for segmenting lecture videos into topic units in order to organize the videos for browsing and to provide search capability. Automatic segmentation is highly desired because of the high cost of manual segmentation. While a lot of research has been conducted on topic segmentation of transcribed spoken text, most attempts rely on domain-specific cues and formal presentation format, and require extensive training; none of these features exist in lecture videos with unscripted and spontaneous speech. In addition, lecture videos usually have few scene changes, which implies that the visual information that most video segmentation methods rely on is not available. Furthermore, even when there are scene changes, they do not match with the topic transitions. In this paper, we make use of the transcribed speech text extracted from the audio track of video to segment lecture videos into topics. We review related research and propose a new segmentation approach. Our approach utilizes features such as noun phrases and combines multiple content-based and discourse-based features. Our preliminary results show that the noun phrases are salient features and the combination of multiple features is promising to improve segmentation accuracy.
Persistent Identifierhttp://hdl.handle.net/10722/47076
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorLin, Men_HK
dc.contributor.authorChau, Men_HK
dc.contributor.authorNunamaker Jr, JFen_HK
dc.contributor.authorChen, Hen_HK
dc.date.accessioned2007-10-30T07:06:27Z-
dc.date.available2007-10-30T07:06:27Z-
dc.date.issued2004en_HK
dc.identifier.citationThe 37th Annual Hawaii International Conference on System Sciences Proceedings, Hawaii, 5-8 January 2004en_HK
dc.identifier.issn1060-3425en_HK
dc.identifier.urihttp://hdl.handle.net/10722/47076-
dc.description.abstractIn multimedia-based e-Learning systems, there are strong needs for segmenting lecture videos into topic units in order to organize the videos for browsing and to provide search capability. Automatic segmentation is highly desired because of the high cost of manual segmentation. While a lot of research has been conducted on topic segmentation of transcribed spoken text, most attempts rely on domain-specific cues and formal presentation format, and require extensive training; none of these features exist in lecture videos with unscripted and spontaneous speech. In addition, lecture videos usually have few scene changes, which implies that the visual information that most video segmentation methods rely on is not available. Furthermore, even when there are scene changes, they do not match with the topic transitions. In this paper, we make use of the transcribed speech text extracted from the audio track of video to segment lecture videos into topics. We review related research and propose a new segmentation approach. Our approach utilizes features such as noun phrases and combines multiple content-based and discourse-based features. Our preliminary results show that the noun phrases are salient features and the combination of multiple features is promising to improve segmentation accuracy.en_HK
dc.format.extent272398 bytes-
dc.format.extent2605 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherI E E E, Computer Society. The Journal's web site is located at http://csdl2.computer.org/persagen/DLPublication.jsp?pubtype=p&acronym=HICSSen_HK
dc.relation.ispartofProceedings of the Hawaii International Conference on System Sciencesen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectComputersen_HK
dc.subjectComputer systemsen_HK
dc.titleSegmentation of lecture videos based on text: A method combining multiple linguistic featuresen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1060-3425&volume=&spage=&epage=&date=2004&atitle=Segmentation+of+Lecture+Videos+Based+on+Text:+A+Method+Combining+Multiple+Linguistic+Featuresen_HK
dc.identifier.emailChau, M: mchau@hkucc.hku.hken_HK
dc.identifier.authorityChau, M=rp01051en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/HICSS.2004.1265045en_HK
dc.identifier.scopuseid_2-s2.0-12344273358en_HK
dc.identifier.hkuros91971-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-12344273358&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume37en_HK
dc.identifier.spage23en_HK
dc.identifier.epage32en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLin, M=26643343200en_HK
dc.identifier.scopusauthoridChau, M=7006073763en_HK
dc.identifier.scopusauthoridNunamaker Jr, JF=7005361041en_HK
dc.identifier.scopusauthoridChen, H=8871373800en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats