We propose an efficient dialogue management for an information navigation system based on a document knowledge base. It is expected that incorporation of appropriate N-best candidates of ASR and contextual information will improve the system performance. The system also has several choices in generating responses or confirmations. In this paper, this selection is optimized as minimization of Bayes risk based on reward for correct information presentation and penalty for redundant turns. We have evaluated this strategy with our spoken dialogue system "Dialogue Navigator for Kyoto City", which also has question-answering capability. Effectiveness of the proposed framework was confirmed in the success rate of retrieval and the average number of turns for information access.
Bibliographic reference. Misu, Teruhisa / Kawahara, Tatsuya (2007): "Bayes risk-based optimization of dialogue management for document retrieval system with speech interface", In INTERSPEECH-2007, 2705-2708.