Travel guide bot proposing various sightseeing spots

Abstract

This paper reports on the travel guidance dialogue system developed for the Task Track of Dialogue System Live Competition 7. This system is based on Remdis and MMDAgent-EX and is designed to assist users in selecting an optimal travel destination by providing diverse candidate sightseeing locations. To manage the dialogue flow, the system utilizes a state transition diagram, dynamically generating and assigning prompts to effectively control interactions. For selecting candidate sightseeing locations, it employs GPT-4o fine-tuned with supervised learning using sightseeing data and applies the Chain-of-Thought (CoT) method to extract relevant locations. Additionally, the system incorporates Travel Viewer, which displays a standard set of 45 sightseeing images and maps on the screen, along with their descriptions, to support users in making informed travel decisions. Furthermore, this paper analyzes user evaluations from the preliminary round of Dialogue System Live Competition 7 and explores the design of an optimal travel guidance chatbot.