Abstract
Text-writing robots have been used in assistive writing and drawing applications. However, robots do not convey emotional tones in the writing process due to the lack of behaviors humans typically adopt. To examine how people interpret designed robotic expressions of emotion through both movements and textual output, we used a pen-plotting robot to generate texts by performing human-like behaviors like stop-and-go, speed, and pressure variation. We examined how people convey emotion in the writing process by observing how they wrote in different emotional contexts. We then mapped these human expressions during writing to the handwriting robot and measured how well other participants understood the robot's affective expression. We found that textual output was the strongest determinant of participants' ability to perceive the robot's emotions, whereas parameters of gestural movements of the robots like speed, fluency, pressure, size, and acceleration could be useful for understanding the context of the writing expression.
Abstract (translated)
文本写作机器人已经被应用于辅助写作和绘图应用程序中。然而,由于机器人缺乏人类通常采取的行为,因此在写作过程中无法传达情感语调。为了检查人们通过运动和文本输出如何解释设计的情感机器人表达,我们使用一支笔绘图机器人,通过执行类似于停格、速度变化和压力变化等人类行为来生成文本。我们检查了人们在写作过程中如何传达情感,通过观察他们在不同的情感背景下如何写作来进行。随后,我们将这些人类表达在写作中映射到手写机器人,并测量其他参与者如何理解机器人的情感表达。我们发现,文本输出是参与者感知机器人情感能力最强的决定性因素,而机器人的运动参数,如速度、流畅度、压力、大小和加速,对于理解写作表达的背景也非常重要。
URL
https://arxiv.org/abs/2302.05959
