An efficient search function based on topic estimation was integrated to our spoken dialogue system for academic document information retrieval. The following two points were mainly studied: 1) to properly categorize documents (to be retrieved) into related topics, and 2) to facilitate retrieval process using topic knowledge. For the first point, a method was developed to calculate recursively the relevance scores of retrieval words and documents for topics. Effects of the recursive process were proved through experimental results; better classification of retrieval words and documents into topics was realized. As for the second point, retrieval range was limited into topics estimated from retrieval words. It was shown through experiments of retrieval task solving that necessary number of dialogue turns (therefore, period of dialogue) could be largely reduced by the range limitation; a smooth retrieval process was proved to be realized using topic knowledge.
Cite as: Kiriyama, S., Hirose, K., Minematsu, N. (2001) Use of topic knowledge in spoken dialogue information retrieval system for academic documents. Proc. 7th European Conference on Speech Communication and Technology (Eurospeech 2001), 1315-1318, doi: 10.21437/Eurospeech.2001-340
@inproceedings{kiriyama01_eurospeech,
author={Shinya Kiriyama and Keikichi Hirose and Nobuaki Minematsu},
title={{Use of topic knowledge in spoken dialogue information retrieval system for academic documents}},
year=2001,
booktitle={Proc. 7th European Conference on Speech Communication and Technology (Eurospeech 2001)},
pages={1315--1318},
doi={10.21437/Eurospeech.2001-340}
}