Kühne Katharina, Herbold Erika, Bendel Oliver, Zhou Yuefang, Fischer Martin H
Division of Cognitive Sciences, University of Potsdam, Potsdam, Germany.
School of Business FHNW, Brugg-Windisch, Brugg, Switzerland.
Front Robot AI. 2024 Jan 29;10:1241519. doi: 10.3389/frobt.2023.1241519. eCollection 2023.
Robots are increasingly used as interaction partners with humans. Social robots are designed to follow expected behavioral norms when engaging with humans and are available with different voices and even accents. Some studies suggest that people prefer robots to speak in the user's dialect, while others indicate a preference for different dialects. Our study examined the impact of the Berlin dialect on perceived trustworthiness and competence of a robot. One hundred and twenty German native speakers ( = 32 years, = 12 years) watched an online video featuring a NAO robot speaking either in the Berlin dialect or standard German and assessed its trustworthiness and competence. We found a positive relationship between participants' self-reported Berlin dialect proficiency and trustworthiness in the dialect-speaking robot. Only when controlled for demographic factors, there was a positive association between participants' dialect proficiency, dialect performance and their assessment of robot's competence for the standard German-speaking robot. Participants' age, gender, length of residency in Berlin, and device used to respond also influenced assessments. Finally, the robot's competence positively predicted its trustworthiness. Our results inform the design of social robots and emphasize the importance of device control in online experiments.
机器人越来越多地被用作与人类的互动伙伴。社交机器人被设计为在与人类互动时遵循预期的行为规范，并且有不同的声音甚至口音。一些研究表明，人们更喜欢机器人用用户的方言说话，而另一些研究则表明人们更喜欢不同的方言。我们的研究考察了柏林方言对机器人可信赖度和能力感知的影响。120名以德语为母语的德国人（平均年龄 = 32岁，标准差 = 12岁）观看了一段在线视频，视频中一个NAO机器人用柏林方言或标准德语说话，并对其可信赖度和能力进行了评估。我们发现，参与者自我报告的柏林方言熟练程度与说方言机器人的可信赖度之间存在正相关关系。只有在控制了人口统计学因素后，参与者的方言熟练程度、方言表现与他们对说标准德语机器人能力的评估之间才存在正相关。参与者的年龄、性别、在柏林的居住时间以及用于回应的设备也会影响评估结果。最后，机器人的能力对其可信赖度有正向预测作用。我们的研究结果为社交机器人的设计提供了参考，并强调了在线实验中设备控制的重要性。
