Learning Japanese with Jouzu: Interaction Outcomes with Stylized Dialogue Fictional Agents

This study investigates how stylized, voiced agents shape user interaction in a multimodal language learning environment. We conducted a mixed-methods evaluation of 54 participants interacting with anime-inspired characters powered by large language models and expressive text-to-speech synthesis. These agents responded in Japanese character language, offering users asynchronous, semi-structured conversation in varying speech styles and emotional tones. We analyzed user engagement patterns, perceived usability, emotional responses, and learning behaviors, with particular attention to how agent stylization influenced interaction across language proficiency levels and cultural backgrounds. Our findings reveal that agent design, especially voice, persona, and linguistic style, substantially affected user experience, motivation, and strategy. This work contributes to the understanding of affective, culturally stylized agents in human-agent interaction and offers guidance for designing more engaging, socially responsive systems.