让机器人更自然地聊家常，提升人机互动的亲密度。
More than Chit-Chat: Developing Robots for Small-Talk Interactions
- 用自动反馈机制引导大模型生成符合社交惯例的闲聊内容。
- 实验证明系统能显著提升闲聊的真实感与自然度。
- 适合做社交机器人、人机交互研究的团队参考。
除了形式上的礼貌，闲聊在社会互动中起着关键作用，是建立关系和理解的口头握手。对于对话式人工智能和社交机器人而言，具备闲聊能力可增强其亲和力，使用户交互更舒适自然。本研究评估了当前大型语言模型（LLMs）驱动社交机器人闲聊的能力，并识别出改进的关键方向。我们提出一种新方法，可自主生成反馈，确保大模型输出符合闲聊规范。通过聊天机器人交互和人-机器人交互多轮评估，证明该系统能有效引导大模型生成真实、自然、类人的闲聊回复。
原文摘要 · Abstract (English)
Beyond mere formality, small talk plays a pivotal role in social dynamics, serving as a verbal handshake for building rapport and understanding. For conversational AI and social robots, the ability to engage in small talk enhances their perceived sociability, leading to more comfortable and natural user interactions. In this study, we evaluate the capacity of current Large Language Models (LLMs) to drive the small talk of a social robot and identify key areas for improvement. We introduce a novel method that autonomously generates feedback and ensures LLM-generated responses align with small talk conventions. Through several evaluations -- involving chatbot interactions and human-robot interactions -- we demonstrate the system's effectiveness in guiding LLM-generated responses toward realistic, human-like, and natural small-talk exchanges.
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