4 papers
Multimodal Rapport Estimation in Real-World HRI
Akihiro Sakuramoto, Takato Hayashi, Ryo Miyoshi +2
Evaluating interaction quality in real-world HRI is an important challenge. If interaction quality can be estimated reliably, the results can be used to improve dialogue strategies…
Breaking the 15% Barrier: A Real-World Data-Driven System for Proactive Social Robot Triggered by User Nonverbal Cues
Yuga Yano, Yuki Okafuji, Ryo Miyoshi +2
Service robots in retail stores increasingly rely on cascaded speech pipelines (STT-LLM-TTS), yet many customer-robot interactions are initiated or guided by nonverbal behaviors su…
User Experience Estimation in Human-Robot Interaction Via Multi-Instance Learning of Multimodal Social Signals
Ryo Miyoshi, Yuki Okafuji, Takuya Iwamoto +2
In recent years, the demand for social robots has grown, requiring them to adapt their behaviors based on users' states. Accurately assessing user experience (UX) in human-robot in…
Whom to Respond To? A Transformer-Based Model for Multi-Party Social Robot Interaction
He Zhu, Ryo Miyoshi, Yuki Okafuji
Prior human-robot interaction (HRI) research has primarily focused on single-user interactions, where robots do not need to consider the timing or recipient of their responses. How…