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

翻译：我们介绍了为2023年对话机器人竞赛（DRC2023）开发的系统。首先，基于规则的语句选择与利用大型语言模型（LLM）的语句生成相结合。这既保证了系统语句的质量，又能应对用户意外的语句。其次，通过考虑基于BERT的是/否分类器和情感估计器的结果来控制对话流程。这使得系统能够根据用户调整状态转换和观光计划。