We propose a cross-media lecture-on-demand system, in which users can selectively view specific segments of lecture videos by submitting text queries. Users can easily formulate queries by using the textbook associated with a target lecture, even if they cannot come up with effective keywords. Our system extracts the audio track from a target lecture video, generates a transcription by large vocabulary continuous speech recognition, and produces a text index. Experimental results showed that by adapting speech recognition to the topic of the lecture, the recognition accuracy increased and the retrieval accuracy was comparable with that obtained by human transcription.
Cite as: Fujii, A., Itou, K., Akiba, T., Ishikawa, T. (2003) A cross-media retrieval system for lecture videos. Proc. 8th European Conference on Speech Communication and Technology (Eurospeech 2003), 1149-1152, doi: 10.21437/Eurospeech.2003-374
@inproceedings{fujii03_eurospeech,
author={Atsushi Fujii and Katunobu Itou and Tomoyosi Akiba and Tetsuya Ishikawa},
title={{A cross-media retrieval system for lecture videos}},
year=2003,
booktitle={Proc. 8th European Conference on Speech Communication and Technology (Eurospeech 2003)},
pages={1149--1152},
doi={10.21437/Eurospeech.2003-374}
}