使用安卓机器人探索Mehrabian的通信模型
Wataru Sato1, Koh Shimokawa2, Takashi Minato3
1Psychological Process Research Team, Guardian Robot Project, RIKEN, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto, 619-0288, Japan. wataru.sato.ya@riken.jp.
Scientific reports
|July 17, 2025
概括
面部表情在面对面沟通中具有最大的情感影响,其次是语音和口头表达. 这项研究证实了Mehrabian的有效性.
科学领域:
- 人与计算机的交互
- 情感计算是一种情感计算.
- 社会心理学 社会心理学
背景情况:
- 多式情绪表达对于有效的人际沟通至关重要.
- 以前的研究,就像Mehrabian的模型一样,提出了面部,声音和口头暗示的情绪影响的等级,但在面对面的环境中缺乏全面的实验验证.
- 人类表演能力的局限性阻碍了研究同时检查所有三种情绪表达方式的研究.
研究的目的:
- 实验性地研究面部,声音和口头表情在受控的面对面场景中的相对情感影响.
- 通过使用安卓来解决人类行动的局限性,以产生一致的情绪表达.
- 为了验证Mehrabian关于不同沟通方式间情感影响等级的模型.
主要方法:
- 一个机器人 (尼古拉) 被编程为系统地显示正面,中性和负面情绪的明显的面部,声音和口头表达.
- 参与者与机器人进行了面对面的互动,并评价了其表情的情感价值.
- 使用人类评分器和ChatGPT进行了比较实验,以评估单模式情感价值.
主要成果:
- 面部表情被列为具有最高的情感影响,其次是语音表达,然后是口头表达.
- 机器人的系统地变化的表达方式允许在各种模式中清晰排名情感影响.
- 面部,声音和口头暗示的单模表情在被人类评分员和ChatGPT评估时显示出相似的情感价值.
结论:
- 这项研究提供了第一个验证Mehrabian模型在面对面环境中的实验证据.
- 面部 (非语言) 表情在面对面沟通中具有最显著的情感影响.
- 机器人可以作为研究人类情绪表达和沟通动态的有效工具.
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