11th Annual Conference of the International Speech Communication Association

Makuhari, Chiba, Japan
September 26-30. 2010

Lecture Subtopic Retrieval by Retrieval Keyword Expansion Using Subordinate Concept

Noboru Kanedera (1), Tetsuo Funada (2), Seiichi Nakagawa (3)

(1) Ishikawa National College of Technology, Japan
(2) Kanazawa University, Japan
(3) Toyohashi University of Technology, Japan

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.

Full Paper

Bibliographic reference.  Kanedera, Noboru / Funada, Tetsuo / Nakagawa, Seiichi (2010): "Lecture subtopic retrieval by retrieval keyword expansion using subordinate concept", In INTERSPEECH-2010, 1281-1284.