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We introduce our system developed for Dialogue Robot Competition 2023(DRC2023). First, rule-based utterance selection and utterance generation usinga large language model (LLM) are combined. We ensure the quality of systemutterances while also being able to respond to unexpected user utterances.Second, dialogue flow is controlled by considering the results of theBERT-based yes/no classifier and sentiment estimator. These allow the system toadapt state transitions and sightseeing plans to the user.

User-adaptive Tourist Information Dialogue System with Yes/No Classifier and Sentiment Estimator