VideoCLEF 2008: ASR classification with wikipedia categories
|VideoCLEF 2008: ASR classification with wikipedia categories|
|Author(s)||Kusrsten J., Richter D., Eibl M.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||Automatic Speech Transcripts, Evaluation, Experimentation, Video Classification (Extra: Classification tasks, k-NN classifier, Speech transcripts, Text classification, Text classifiers, Training data, Video classification, Wikipedia, Classifiers, Experiments, Learning systems, Linguistics, Metadata, Remelting, Translation (languages), Text processing)|
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VideoCLEF 2008: ASR classification with wikipedia categories is a 2009 conference paper written in English by Kusrsten J., Richter D., Eibl M. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
This article describes our participation at the VideoCLEF track. 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. For the text classification the Naive-Bayes and kNN classifier from the WEKA toolkit were used. We submitted experiments for classification task 1 and 2. For the translation of the feeds to English (translation task) Google's AJAX language API was used. Although our experiments achieved only low precision of 10 to 15 percent, we assume those results will be useful in a combined setting with the retrieval approach that was widely used. Interestingly, we could not improve the quality of the classification by using the provided metadata.
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