Effects of Different Types of Social Robot Voices on Affective Evaluations in Different Application Fields

Abstract

As the roles of social robots are increasingly diverse, it is important to design the robots according to their application fields and end-users needs. A robot’s voice is a strong social cue, the design of which can influence people’s affective evaluation and acceptance toward robots. The aim of this study is to investigate the affective evaluation of different robot voices in various application fields, and obtained suitable voice types for robots in different application fields. In particular, this study focused on the three applications (i.e., shopping reception, home companion, and education), investigated the effect of voice types (i.e., male, female, child, and synthetic) of social robots on the affective evaluation of users. Principal component analysis identified three latent influencing factors (i.e., social skills, competence and the state of the interaction relationships). Multivariable analysis proved that for overall acceptance, significant interaction effects existed between robots’ voice types and their application fields. For shopping reception robots, the most acceptable voice type is adult male voice and child voice. For home companion robots, the most acceptable robot voice types are adult male and child voices. For education robots, the most acceptable voice types are adult female and male voices. The results of this study are expected to construct design principles for robot voice design in various applications.