Color-Based Models for Emotions Expressing for Robots: A Vietnamese Pilot Research

This paper presents a study on the applicability of color-based emotional expression models for robots, originally developed for Japanese users, to a Vietnamese demographic. Our research introduces a newly collected dataset capturing Vietnamese participants’ interpretations of robot-emitted colors and gradients, addressing a significant gap in culturally adapted robotic communication. Through two experimental conditions, we evaluate the effectiveness of (1) solid colors and (2) color gradients in conveying eight primary emotions. A total of 330 Vietnamese participants engaged in the study, providing subjective ratings on emotion recognition accuracy. Our findings indicate that while some emotions (e.g. anger and trust) align well with color representations, others (e.g. surprise and disgust) exhibit cultural variations in perception. A one-way ANOVA test confirms statistically significant differences in how emotions are recognized across color models. These results underscore the importance of cultural adaptation in robot emotion expression and highlight potential directions for refining color-based models for cross-cultural applications. Future research will explore neural network-based emotion adaptation to enhance real-time, culturally responsive robotic interactions.