Enhancing Consistency in Multimodal Dialogue System Using LLM with Dialogue Scenario
This work addresses user satisfaction in domain-specific travel agency dialogue systems, but it is incremental as it builds on existing methods with minor improvements.
The paper tackled the problem of enhancing consistency in multimodal dialogue systems for travel planning by using an LLM with dialogue scenarios, resulting in a system that ranked fifth in impression and sixth in plan evaluation among 12 teams in a competition.
This paper describes our dialogue system submitted to Dialogue Robot Competition 2023. The system's task is to help a user at a travel agency decide on a plan for visiting two sightseeing spots in Kyoto City that satisfy the user. Our dialogue system is flexible and stable and responds to user requirements by controlling dialogue flow according to dialogue scenarios. We also improved user satisfaction by introducing motion and speech control based on system utterances and user situations. In the preliminary round, our system was ranked fifth in the impression evaluation and sixth in the plan evaluation among all 12 teams.