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Lecturer(s)
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Sio Joanna Ut-Seong, doc. Ph.D.
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Course content
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(1) Introduction (2) Discourse structure: turn-taking in human conversations (3) Discourse structure: common ground (4) LLM: how does it work? --- Deep Learning (5) LLM: LLM-based robot (6) Prompt engineering (7) Prompt engineering (8) Safety and ethics (9) Interacting with robots and evaluation (I) (10) Interacting with robots and evaluation (II) (11) Multilingal capacities (12) Multilingual interaction (13) Robots as companions
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Learning activities and teaching methods
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unspecified
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Learning outcomes
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This interdisciplinary course explores human communication principles and their application to human-robot interaction. Students engage with discourse analysis, prompt engineering, multilingual AI systems, and ethical considerations in robotics. Graduates will be equipped to contribute to the development of linguistically capable, socially aware, and sustainable AI systems?skills relevant in linguistics, media studies, translation, and tech ethics.
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Prerequisites
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unspecified
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Assessment methods and criteria
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unspecified
(i) Class participation , and (ii) Project (students will be required to (a) set up different prompts for LLM to create different identities for the robot; (b) engage in conversation with the robot, (c) evaluate the interaction and point out aspects different from human-human interaction.)
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Recommended literature
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