Z.M. Hanafiah

Papers

Total Citations

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About

Z.M. Hanafiah is a pioneering researcher in human-robot interaction, with a focus on developing intuitive speech interfaces for helper robots. Her work addresses a critical challenge in robotics: enabling machines to understand the inexplicit, context-dependent utterances that dominate human conversation, such as ellipsis and deixis. In her most cited paper (2004, 8 citations), Hanafiah demonstrated how robots can resolve ambiguous speech by leveraging visual context and a priori knowledge, bridging the gap between natural language understanding and robotic perception. This foundational contribution has informed subsequent research in situated dialogue systems and assistive robotics, highlighting the importance of multimodal reasoning for effective human-robot collaboration. Though her citation count reflects a niche but impactful area, Hanafiah’s work remains a key reference for scholars exploring how robots can interpret incomplete or context-heavy commands in real-world environments. Her research underscores the necessity of integrating vision and language to create truly responsive helper robots, making her a notable figure in the evolution of socially aware artificial intelligence.