MorphHat: A Humanoid Robot Interpreter for Enhancing Multilingual Collaboration

Multilingual collaboration is increasingly common as today’s world becomes global and culturally diverse. While diversity fosters innovation, language barriers can hinder involvement and effective communication. Prior work has primarily focused on improving translation accuracy with limited attention to how translation systems shape dimensions of trust in interaction. Given that users must rely blindly on technology due to their inability to understand the system’s output, this issue becomes a crucial aspect. To address this gap, we introduce MorphHat, a co-embodied humanoid robot interpreter featuring a customizable, morphing face that visually represents the active speaker. We evaluated MorphHatMorphHat influenced trust, rapport, and social presence. We discuss these insights as early design implications for future embodied translation systems.