Younggwan Kim
Papers
1
Total Citations
6
H-Index
1
About
Younggwan Kim is a researcher whose work focuses on advancing speech recognition technologies for human-robot interaction, particularly in challenging acoustic environments. His key research areas include distant multi-channel speech processing, noise-robust automatic speech recognition, and the development of specialized databases for conversational robots. Kim's most notable contribution is his foundational work on creating the Korean distant multi-channel speech and noise databases, designed to improve speech recognition accuracy for indoor conversational robots. This database, detailed in his 2017 paper, addresses the critical challenge of capturing clear speech from a distance amidst ambient noise—a common hurdle in real-world robotic applications. While his most-cited paper has garnered 6 citations, its impact lies in providing a standardized resource that enables other researchers to develop and benchmark more robust speech recognition systems. Kim's work is particularly significant for advancing the practicality of voice-controlled robots in homes and workplaces, where reliable speech understanding is essential for natural interaction. His contributions help bridge the gap between laboratory speech recognition and real-world deployment, making him a valuable figure in the field of human-robot communication.
Research Focus
Key Achievements
Top Papers
- 1