@inproceedings{c3311ba776e7464485e2eaf1cd22c8de,
title = "Classifying topics of video lecture contents using speech recognition technology",
abstract = "We explore a speech-based topic classification approach. We generate the transcript of input video lecture based on speech recognition technology and identify the topic by comparing its term-based vector with topic models. The preliminary experiment result shows that the speech-based topic classification works well, with its performance comparable to one that directly uses manual transcripts. The approach also shows robustness against speech recognition errors up to 40.6%.",
keywords = "Speech recognition, Tf-idf, Topic classification, Topic modeling",
author = "Jun Park and Jihie Kim",
year = "2012",
doi = "10.1007/978-3-642-30950-2_125",
language = "English",
isbn = "9783642309496",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "694--695",
booktitle = "Intelligent Tutoring Systems - 11th International Conference, ITS 2012, Proceedings",
note = "11th International Conference on Intelligent Tutoring Systems, ITS 2012 ; Conference date: 14-06-2012 Through 18-06-2012",
}