Chen-Kang Wang
Papers
1
Total Citations
2
H-Index
1
About
Chen-Kang Wang is a pioneering researcher in robotics audition and embedded signal processing, with a focus on enabling machines to hear and interpret sound in real-world environments. His most-cited work, "Sound source tracking and speech enhancement by microphone array on an embedded dual-core processor platform," introduces a compact, efficient robot audition module that integrates voice activity detection, sound source localization, and speech enhancement on a dual-core ARM-DSP platform. This contribution is foundational for deploying intelligent hearing in autonomous systems, bridging the gap between algorithmic complexity and real-time hardware constraints. Though his citation count is modest, Wang’s work is notable for its practical engineering impact, demonstrating how embedded processors can handle computationally intensive audio tasks in noisy, dynamic settings—a critical step toward responsive human-robot interaction. His research underscores the importance of hardware-software co-design in robotics, offering a template for low-power, high-performance auditory perception systems. Wang’s achievements highlight his role in advancing the feasibility of robot audition beyond controlled laboratory conditions, making him a key figure in the evolution of autonomous listening technologies.
Research Focus
Key Achievements
Top Papers
- 1