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VideoCLEF 2008: ASR Classification with Wikipedia Categories [chapter]

Jens Küsrsten, Daniel Richter, Maximilian Eibl
2009 Lecture Notes in Computer Science  
This article describes our participation at the VideoCLEF track of the CLEF campaign 2008. We designed and implemented a prototype for the classification of the Video ASR data.  ...  Our approach was to regard the task as text classification problem. We used terms from Wikipedia categories as training data for our text classifiers.  ...  Conclusion and Future Work The experiments showed that the classification of dual-language video based on ASR transcripts is a quite hard task.  ... 
doi:10.1007/978-3-642-04447-2_123 fatcat:wu33ssqhfzey7lc3p5tmcledlm

Overview of VideoCLEF 2008: Automatic Generation of Topic-Based Feeds for Dual Language Audio-Visual Content [chapter]

Martha Larson, Eamonn Newman, Gareth J. F. Jones
2009 Lecture Notes in Computer Science  
The videos were grouped by class label into topic-based RSS-feeds, displaying title, description and keyframe for each video. Five groups participated in the 2008 VideoCLEF track.  ...  The VideoCLEF track, introduced in 2008, aims to develop and evaluate tasks related to analysis of and access to multilingual multimedia content.  ...  Conclusions and Future Plans The Vid2RSS task in the VideoCLEF 2008 track involved classification, translation and keyframe extraction performed on dual language video.  ... 
doi:10.1007/978-3-642-04447-2_119 fatcat:rr2cv7ngmjfxxdncygjv2xfwkq

UAIC: Participation in VideoCLEF Task

Tudor-Alexandru Dobrila, Mihail-Ciprian Diaconasu, Irina-Diana Lungu, Adrian Iftene
2009 Conference and Labs of the Evaluation Forum  
For first task we created two resources starting from Wikipedia pages and pages identified with Google and used two tools for classification: Lucene and Weka.  ...  This year marked UAIC 1 's first participation at the VideoCLEF competition. Our group built two separated systems for tasks "Subject Classification" and "Affect Detection".  ...  This is why our approach is based on two aspects of the video: the sound and the ASR transcript.  ... 
dblp:conf/clef/DobrilaDLI09a fatcat:7jq77hqnzzbpjnkzkckypmu34y

Overview of VideoCLEF 2009: New Perspectives on Speech-Based Multimedia Content Enrichment [chapter]

Martha Larson, Eamonn Newman, Gareth J. F. Jones
2010 Lecture Notes in Computer Science  
The Subject Classification Task involved automatic tagging of videos with subject theme labels.  ...  VideoCLEF 2009 offered three tasks related to enriching video content for improved multimedia access in a multilingual environment.  ...  The VideoCLEF 2009 Subject Classification Task ran on TRECVid 2007 and 2008 data from Beeld & Geluid.  ... 
doi:10.1007/978-3-642-15751-6_46 fatcat:236ipt4d4bacvjl65hljzmmcri

Enhanced Multimedia Content Access and Exploitation Using Semantic Speech Retrieval

Roeland Ordelman, Franciska de Jong, Martha Larson
2009 2009 IEEE International Conference on Semantic Computing  
This paper provides an overview of techniques and trends in semantic speech retrieval, which is taken to encompass all approaches offering meaning-based access to spoken word collections.  ...  We conclude with an overview of the challenges for semantic speech retrieval in the workflow of a real-world archive and perspectives on future tasks in which speech retrieval integrates information related  ...  ACKNOWLEDGMENT This paper is based on research that was partly funded by IST project MESH ( and by bsik program MultimediaN (  ... 
doi:10.1109/icsc.2009.80 dblp:conf/semco/OrdelmanJL09 fatcat:4wbj4qm7uffnvp5rhmdxex4acq

The Importance of being Grid: Chemnitz University of Technology at Grid@CLEF

Maximilian Eibl, Jens Kürsten
2009 Conference and Labs of the Evaluation Forum  
One run one was a fusion run combining the results of the four other experiments.  ...  Whereas the different runs demonstrated that the impact of the used retrieval technologies is highly depending on the corpus, the merged approach produced the best results in each language.  ...  VideoCLEF The Xtrieval framework was adapted for the classification of the Video ASR data. We regarded the task as a text classification problem.  ... 
dblp:conf/clef/EiblK09 fatcat:scbrtgcoarfyrcuoboy3htknmi