Abstract
We developed a supporting system for creation of educational video contents. The system automatically segments a lecture video material into subtopics based on speech signals by a statistical model for text segmentation. In this paper, we reports on the result of retrieving the lecture subtopics by keyword expansion using the knowledge of the dictionary, and so on. The keyword expansion using the subordinate concept improved the average reciprocal order (MRR:Mean Reciprocal Rank) from 0.51 to 0.55 when subtopics are retrieved by a set of three search keywords for the lecture voice text recognized by automatic speech recognition. Index Terms: subtopic retrieval, keyword expansion, automatic speech recognition, lecture video
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