Cherie Sew
Papers
1
Total Citations
13
H-Index
1
About
Cherie Sew is a rising researcher at the intersection of human-robot interaction and computational pragmatics, whose work explores how robots can understand and use the nuanced, indirect ways humans naturally communicate. Her most-cited paper, "Can you pass that tool?: Implications of Indirect Speech in Physical Human-Robot Collaboration" (2025, 13 citations), investigates how indirect speech acts (ISAs)—such as phrasing a request as a question rather than a command—affect collaboration fluency and user trust. This work is foundational in moving beyond simple, explicit voice commands toward more natural, socially intelligent robot behavior. Sew’s contributions are particularly significant for physical collaboration scenarios, where subtle linguistic cues can improve teamwork and reduce cognitive load. Though early in her career, her research has already garnered attention for bridging linguistics and robotics, with implications for assistive technologies, manufacturing, and service robots. By tackling the pragmatic challenges of human-robot dialogue, Sew is helping shape a future where machines can interpret not just what we say, but how we say it.
Research Focus
Key Achievements
Top Papers
- 1