Android机器人发声情感表达与评价过程中的运动生成

C. Ishi
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引用次数: 0

摘要

在自然的对话互动中,经常会出现笑声和惊讶等声音情感表达,为了实现机器人介导的顺畅沟通,这些情感表达是需要考虑的重要因素。如果音频和视觉模式不匹配,可能会导致沟通不畅,尤其是在具有高度人性化外观的机器人中。在本章中,基于人类在对话互动中的行为分析结果,介绍了笑声和发声惊喜事件的运动生成方法。使用机器人来评估控制面部、头部和上半身的不同模式(眉毛抬高、眼皮扩大/缩小、嘴角/脸颊抬高、眨眼、头部运动和躯干运动控制)和不同运动控制水平的有效性。主观实验表明,每种形态在感知运动自然性(人类相似)和情感表达程度方面的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Motion Generation during Vocalized Emotional Expressions and Evaluation in Android Robots
Vocalized emotional expressions such as laughter and surprise often occur in natural dialogue interactions and are important factors to be considered in order to achieve smooth robot-mediated communication. Miscommunication may be caused if there is a mismatch between audio and visual modalities, especially in android robots, which have a highly humanlike appearance. In this chapter, motion generation methods are introduced for laughter and vocalized surprise events, based on analysis results of human behaviors during dialogue interactions. The effectiveness of controlling different modalities of the face, head, and upper body (eyebrow raising, eyelid widening/narrowing, lip corner/cheek raising, eye blinking, head motion, and torso motion control) and different motion control levels are evaluated using an android robot. Subjective experiments indicate the importance of each modality in the perception of motion naturalness (humanlikeness) and the degree of emotional expression.
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