A classifier-based approach to supporting the augmentation of the question-answer database for spoken dialogue systems

Authors:
Hiromi Narimatsu;Mikio Nakano;Kotaro Funakoshi
Affiliations:
The University of Electro-Communications, Japan;Honda Research Institute Japan Co., Ltd., Japan;Honda Research Institute Japan Co., Ltd., Japan
Venue:
IWSDS'10 Proceedings of the Second international conference on Spoken dialogue systems for ambient environments
Year:
2010

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Cited 1

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Abstract

Dealing with a variety of user questions in question-answer spoken dialogue systems requires preparing as many question-answer patterns as possible. This paper proposes a method for supporting the augmentation of the question-answer database. It uses user questions collected with an initial question-answer system, and detects questions that need to be added to the database. It uses two language models; one is built from the database and the other is a large-vocabulary domain-independent model. Experimental results suggest the proposed method is effective in reducing the amount of effort for augmenting the database when compared to a baseline method that used only the initial database.