通过非语言行为分析，提升AI对小组协作中共同认知与参与度的理解。
Speech Is Not Enough: Interpreting Nonverbal Indicators of Common Knowledge and Engagement
- 融合语音与非语言行为，实时追踪学生课堂互动状态。
- 可识别协作中的共同认知水平与个体参与度变化。
- 适合教育场景下的智能助教系统开发与研究者参考。
本研究旨在开发能够支持小组问题解决与社交动态的AI伙伴。在多方协作环境中，多模态分析对于识别组员的非语言互动至关重要。结合言语参与情况，可全面理解协作与参与度，为AI伙伴提供必要上下文。本次演示展示了我们在检测和跟踪学生任务导向课堂互动中非语言行为方面的现有能力，及其对追踪共同认知与参与度的影响。
原文摘要 · Abstract (English)
Our goal is to develop an AI Partner that can provide support for group problem solving and social dynamics. In multi-party working group environments, multimodal analytics is crucial for identifying non-verbal interactions of group members. In conjunction with their verbal participation, this creates an holistic understanding of collaboration and engagement that provides necessary context for the AI Partner. In this demo, we illustrate our present capabilities at detecting and tracking nonverbal behavior in student task-oriented interactions in the classroom, and the implications for tracking common ground and engagement.
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