Table1_“Ick bin een Berlina”: dialect proficiency impacts a robot’s trustworthiness and competence evaluation.pdf

Background: 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.
Methods: Our study examined the impact of the Berlin dialect on perceived trustworthiness and competence of a robot. One hundred and twenty German native speakers (Mage = 32 years, SD = 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.
Results: 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.
Discussion: Our results inform the design of social robots and emphasize the importance of device control in online experiments.

研究背景：机器人作为人类交互伙伴的应用场景日益增多。社交机器人被设计为在与人类互动时遵循既定行为规范，且可配备不同音色乃至口音。部分研究表明用户更偏好机器人使用自身母语方言进行交流，而另有研究则显示人们更倾向于使用非自身母语的方言。
研究方法：本研究探讨了柏林方言对机器人感知可信度与能力评价的影响。招募120名以德语为母语的被试（平均年龄M=32岁，标准差SD=12岁），让其观看一段包含NAO机器人的在线视频，该机器人分别使用柏林方言或标准德语进行发言，随后被试需对机器人的可信度与能力水平进行评分。
研究结果：本研究发现，被试自我报告的柏林方言熟练度与对使用该方言的机器人的可信度评价呈正相关。仅在控制人口统计学变量后，被试的方言熟练度、方言使用表现与对使用标准德语的机器人的能力评价之间才存在正相关关联。被试的年龄、性别、在柏林的居住时长以及作答所用设备，同样会对其评价结果产生影响。最终，机器人的能力水平可正向预测其可信度评价。
讨论：本研究结果可为社交机器人的设计提供参考，并强调了在线实验中设备控制环节的重要性。