We demonstrate an embodied conversational agent that can function as a receptionist and generate a mixture of open and closed-domain dialogue along with facial expressions, by using a large language model (LLM) to develop an engaging conversation. We deployed the system onto a Furhat robot, which is highly expressive and capable of using both verbal and nonverbal cues during interaction. The system was designed specifically for the National Robotarium to interact with visitors through natural conversations, providing them with information about the facilities, research, news, upcoming events, etc. The system utilises the state-of-the-art GPT-3.5 model to generate such information along with domain-general conversations and facial expressions based on prompt engineering.

翻译：我们展示了一个具备接待员功能的具身会话智能体，该智能体通过使用大语言模型（LLM）生成融合开放域与封闭域对话及面部表情的交互，从而构建引人入胜的对话体验。该系统被部署于具有高度表现力、能在交互中运用言语与非言语线索的Furhat机器人上。系统专为National Robotarium设计，可通过自然对话与访客互动，提供关于设施、研究、新闻、近期活动等信息的咨询服务。该系统采用前沿的GPT-3.5模型，通过提示工程生成上述信息及通用领域对话与面部表情。