Papers
4
Total Citations
22
H-Index
3
About
Sukyung Seok investigates the intersection of human-robot interaction (HRI), cross-cultural communication, and language assessment, with a focus on how robots can understand and respond to human social cues. Her most cited work (12 citations) reveals cultural differences in politeness, showing that native English and Korean speakers use indirect speech acts differently when requesting robots—a finding critical for designing culturally adaptive AI. She also pioneered robot-assisted language assessment (5 citations), developing and evaluating a system for cognitive and language screening, addressing a gap in mental health care robotics. Her research on non-lexical backchannels (e.g., “mm-hmm” in Korean) demonstrates that conversational context and social relations shape user perception of robot empathy, and she has built predictive models for such nonverbal feedback. By blending linguistics, social psychology, and robotics, Seok’s work advances socially aware machines that navigate cultural nuance, with implications for global HRI design and accessible healthcare technology. Her studies, though early in citation impact, lay groundwork for robots that communicate with genuine cultural sensitivity.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4