A reduced-dimensionality approach to uncovering dyadic modes of body motion in conversations

Face-to-face conversations are central to human communication and a fascinating example of joint action. Beyond verbal content, one of the primary ways in which information is conveyed in conversations is body language. Body motion in natural conversations has been difficult to study precisely due to the large number of coordinates at play. There is need for fresh approaches to analyze and understand the data, in order to ask whether dyads show basic building blocks of coupled motion. Here we present a method for analyzing body motion during joint action using depth-sensing cameras, and use it to analyze a sample of scientific conversations. Our method consists of three steps: defining modes of body motion of individual participants, defining dyadic modes made of combinations of these individual modes, and lastly defining motion motifs as dyadic modes that occur significantly more often than expected given the single-person motion statistics. As a proof-of-concept, we analyze the motion...

面对面交谈是人类交流的核心形式，亦是联合行动的典型范例。除却语言内容，肢体语言是交谈中传递信息的主要途径之一。自然交谈中的肢体动作因涉及大量待分析的坐标参数，难以实现精准研究。因此亟需全新的数据分析方法，以探究双人交互组是否存在协同动作的基本构成单元。本研究提出一种基于深度传感相机的联合行动肢体动作分析方法，并将其应用于科学交谈样本的分析。本方法共包含三个步骤：一是定义单个参与者的肢体动作模式，二是定义由上述单人动作模式组合而成的双人交互动作模式，三是将基于单人动作统计数据预期出现频率显著更高的双人交互动作模式定义为动作基元（motion motifs）。作为概念验证，我们对该类动作展开了分析……