Teleoperating social robots requires operators to ``speak as the robot,'' as local users would favor robots whose appearance and voice match. This study focuses on real-time altered auditory feedback (AAF), a method to transform the acoustic traits of one's speech and provide feedback to the speaker, to transform the operator's self-representation toward ``becoming the robot.'' To explore whether AAF with voice transformation (VT) matched to the robot's appearance can influence the operator's self-representation and ease the task, we experimented with three conditions: no VT (No-VT), only VT (VT-only), and VT with AAF (VT-AAF), where participants teleoperated a robot to verbally serve real passersby at a bakery. The questionnaire results demonstrate that VT-AAF changed the participants' self-representation to match the robot's character and improved participants' subjective teleoperating experience, while task performance and implicit measures of self-representation were not significantly affected. Notably, 87\% of the participants preferred VT-AAF the most.
https://doi.org/10.1145/3613904.3642561
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)