Tourist Attraction Recommendation System using Dialogue Management based on State Transition and LLM-based Response Generation

Abstract

This paper describes our system submitted for the task track of the Dialogue System Live Competition 7. In task-oriented dialogue systems, dialogue management with LLM sometimes fails to achievetask completion. For this problem, we combine rule-based dialogue management by DialBB and response generation by LLM. This enables the system to reliably determine tourist attraction while maintaining flexibility in conversation. In addition, we use a VAD instead of the Remdis built-in VAP, because unnecessary interruptions by the system occurred while the user was speaking. In the preliminary round, our system received positive feedback from the users when the dialogue was successfully completed without trouble.