Yunju Baek
Papers
1
Total Citations
8
H-Index
1
About
Yunju Baek is a leading researcher at the intersection of child-robot interaction and natural language processing, with a primary focus on developing dialogue systems that can genuinely understand and engage with children. Her most-cited work, "Child-Centric Robot Dialogue Systems: Fine-Tuning Large Language Models for Better Utterance Understanding and Interaction" (2024, 8 citations), addresses a critical challenge in human-robot interaction: children's unique linguistic patterns, including syntactic incompleteness, pronunciation inaccuracies, and creative expressions, which often confound standard language models. Baek's major contribution lies in demonstrating how fine-tuning large language models on child-specific speech data can dramatically improve a robot's ability to interpret and respond to young users, enabling more natural, sustained conversational engagement. Her research has significant implications for educational robotics, therapeutic interventions, and assistive technologies for children. By bridging the gap between adult-centric AI systems and children's developmental language stages, Baek is helping to create robots that can serve as patient, understanding companions and tutors. Her work represents a crucial step toward truly child-centered artificial intelligence, where technology adapts to the user rather than the other way around.
Research Focus
Key Achievements
Top Papers
- 1