Akane Matsushima
Papers
1
Total Citations
2
H-Index
1
About
Akane Matsushima is a researcher in cognitive robotics and human-robot interaction, with a focus on how machines can learn the fundamental structures of human communication. Her work centers on the computational modeling of dialogue acts—the illocutionary forces behind utterances like questions, requests, and greetings—and how robotic systems can acquire these skills through social scaffolding. In her most-cited paper, "Scaffolding for a Robot That Learns Reactions to Dialogue Acts" (2018), Matsushima explores the mechanisms by which a robot can learn appropriate responses to dialogue acts, drawing on foundational theories of speech acts (Austin, 1962). She argues that understanding dialogue act learning is essential for advancing artificial cognition, as these acts form the bedrock of human interaction. Though her citation count is modest, her contributions are conceptually significant, bridging linguistics, developmental psychology, and robotics. Matsushima’s work offers a fresh perspective on how robots might not just process language, but genuinely participate in the social dynamics of conversation, laying groundwork for more intuitive and adaptive human-robot collaboration.
Research Focus
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Top Papers
- 1Scaffolding for a Robot That Learns Reactions to Dialogue Acts2 citations · 2018