"Ick bin een Berlina":方言熟练程度会影响机器人的可信度和能力评估
Katharina Kühne1, Erika Herbold1, Oliver Bendel2
1Division of Cognitive Sciences, University of Potsdam, Potsdam, Germany.
Frontiers in robotics and AI
|February 13, 2024
概括
社交机器人 社交机器人
科学领域:
- 人与机器人的交互
- 社会语言学 社会语言学
- 人工智能的人工智能
背景情况:
- 社交机器人越来越多地与人类互动,具有各种声音和口音.
- 关于用户对机器人方言的偏好研究是混合的,有些人喜欢用户方言,有些人喜欢不同的方言.
- 了解方言对机器人知觉的影响对于有效的人机交互至关重要.
研究的目的:
- 调查柏林方言如何影响对社会机器人的可信度和能力的看法.
- 探索用户的方言熟练程度与他们对机器人特征的评估之间的关系.
- 确定影响对方言说话机器人的看法的人口因素.
主要方法:
- 120名德语母语人士在视频中评估了一个NAO机器人.
- 机器人用柏林方言或标准德语说话.
- 参与者对机器人的可信度和能力进行了评价,并收集了方言熟练程度和人口统计数据.
主要成果:
- 参与者对柏林方言的熟练程度和他们对方言说话机器人的可信度的看法之间发现了积极的相关性.
- 机器人的能力积极预测了它的可信度.
- 年龄,性别和居住地等人口因素影响了机器人评估,方言能力也影响了标准德国机器人的能力评级.
结论:
- 方言在塑造用户对社交机器人可信度和能力的看法方面发挥着重要作用.
- 个人的方言能力和表现可以影响用户如何评估机器人特征.
- 未来的研究应该考虑在线人机交互研究中的人口变量和设备控制.
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