Communication between humans and robots (or virtual agents) is essential for interaction and often inspired by human communication, which uses gestures, facial expressions, gaze direction, and other explicit and implicit means. This work presents an interaction experiment where humans and virtual agents interact through explicit (gestures, manual entries using mouse and keyboard, voice, sound, and information on screen) and implicit (gaze direction, location, facial expressions, and raise of eyebrows) communication to evaluate the effect of mixed explicit-implicit communication against purely explicit communication. Results obtained using Bayesian parameter estimation show that the number of errors and task execution time did not significantly change when mixed explicit and implicit communications were used, and neither the perceived efficiency of the interaction. In contrast, acceptance, sociability, and transparency of the virtual agent increased when using mixed communication modalities (88.3%, 92%, and 92.9% of the effect size posterior distribution of each variable, respectively, were above the upper limit of the region of practical equivalence). This suggests that task-related measures, such as time, number of errors, and perceived efficiency of the interaction, have not been influenced by the communication type in our particular experiment. However, the improvement of subjective measures related to the virtual agent, such as acceptance, sociability, and transparency, suggests that humans are more receptive to mixed explicit and implicit communications.

翻译：人类与机器人（或虚拟代理）之间的通信对于交互至关重要，且常受人类通信方式的启发，即使用手势、面部表情、视线方向及其他显式与隐式手段。本研究设计了一项交互实验，让人类与虚拟代理通过显式（手势、使用鼠标和键盘的手动输入、语音、声音及屏幕信息）和隐式（视线方向、位置、面部表情、挑眉动作）通信进行交互，以评估混合显式-隐式通信相较于纯显式通信的效果。采用贝叶斯参数估计得到的结果表明，当使用混合显式与隐式通信时，错误数量和任务执行时间并未发生显著变化，交互的感知效率亦无显著差异。相比之下，虚拟代理的接受度、社交性和透明度在使用混合通信模式时均有所提升（各变量的效应量后验分布中分别有88.3%、92%和92.9%高于实际等价区域的上限）。这表明在我们特定的实验中，任务相关指标（如时间、错误数量及交互的感知效率）未受通信类型的影响。然而，与虚拟代理相关的主观指标（如接受度、社交性和透明度）的改善表明，人类对混合显式与隐式通信的接受程度更高。