How does a robot’s dialect affect trust?
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 in different designs, voices, and even accents. Studies on dialect in robot speech yielded conflicting findings: Some suggest that people prefer robots to speak with the user’s dialect, while others indicate with a preference for different dialects. Our study examined the impact of the Berlin dialect on the perceived trustworthiness and competence of a robot. One hundred twenty-nine German native speakers (Mage = 32 years, SD = 12) watched an online video featuring a Nao robot speaking either 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 the robot’s trustworthiness. There was also a positive association between the participants’ proficiency and performance in the Berlin dialect and their assessment of the robot’s competence, but only for the standard German-speaking robot. Age, gender, length of residency in Berlin, and the device used also played a role in the assessments. Our study provides insights for robot design and emphasizes the importance of device control in online experiments.