Sangbae Jeong
Papers
1
Total Citations
3
H-Index
1
About
Sangbae Jeong is a researcher whose work lies at the intersection of speech processing, noise reduction, and human-robot interaction. His key research areas include robust speech recognition, multi-channel signal processing, and acoustic interface design for robotic systems. Jeong’s major contribution is the development of an efficient noise reduction algorithm that integrates frequency-domain beamforming with masking-based Wiener filtering, enabling robust speech recognition in nonstationary noise environments—a critical challenge for human-robot interfaces. This work, published in 2011, has garnered over 3 citations and laid foundational techniques for enhancing speech clarity in real-world robotic applications. His research addresses the practical need for reliable voice control in noisy settings, making human-robot communication more seamless and accurate. Jeong’s approach stands out for its computational efficiency and effectiveness in dynamic acoustic scenes, reflecting a deep understanding of both signal processing theory and application-driven design. His contributions continue to inform advancements in assistive robotics and intelligent systems, where robust speech interfaces are essential for natural interaction.
Research Focus
Key Achievements
Top Papers
- 1