In recent years, large language models (LLMs) have rapidly proliferated and
have been utilized in various tasks, including research in dialogue systems. We
aimed to construct a system that not only leverages the flexible conversational
abilities of LLMs but also their advanced planning capabilities to reduce the
speaking load on human interlocutors and efficiently plan trips. Furthermore,
we propose a method that divides the complex task of a travel agency into
multiple subtasks, managing each as a separate phase to effectively accomplish
the task. Our proposed system confirmed a certain level of success by achieving
fourth place in the Dialogue Robot Competition 2023 preliminaries rounds. We
report on the challenges identified through the competition.

我们旨在构建一个系统，不仅利用大型语言模型的灵活对话能力，还利用其先进的规划能力，降低人类对话者的讲话负担并高效地规划行程。我们提出了一种将旅行社的复杂任务划分为多个子任务的方法，将每个子任务作为一个独立阶段进行管理，以有效地完成任务。我们的提出的系统在 2023 年对话机器人比赛的预赛中取得了一定的成功，并报告了比赛中发现的挑战。

发展交互式旅游规划：由大型语言模型驱动的对话机器人系统

Developing Interactive Tourism Planning: A Dialogue Robot System Powered  by a Large Language Mode

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.

这篇论文描述了我们提交给 2023 年对话机器人竞赛的对话系统。该系统旨在帮助旅行社的用户决定参观京都市的两个观光景点的计划。通过根据对话场景控制对话流程，我们的对话系统具有灵活性和稳定性，并根据系统的话语和用户的情况引入动作和语音控制以提高用户满意度。在预赛中，我们的系统在印象评估中排名第五，在计划评估中排名第六，共有 12 支队伍。