Masaaki Fukumoto
Papers
1
Total Citations
14
H-Index
1
About
Masaaki Fukumoto is a leading researcher in humanoid robotics and human-robot interaction, with a particular focus on enhancing robots' perceptual capabilities in real-world environments. His most influential work addresses a critical challenge in household robotics: enabling robots to reliably understand human speech despite their own operational noise. In his highly cited 2019 study, Fukumoto developed innovative signal processing techniques to reduce stationary ego-noise—the persistent sounds generated by a robot's own motors and fans—which significantly degrade the accuracy of third-party automatic speech recognition (ASR) services. By proposing novel noise reduction methods that increase the signal-to-noise ratio, his research has directly improved the listening capability of humanoid robots, making them more practical for home assistance and service applications. With 14 citations on this key paper alone, Fukumoto's contributions have influenced subsequent work in robot audition and noise-robust ASR. His achievements demonstrate a deep understanding of both acoustic engineering and practical robotics, positioning him as a notable figure in the development of more responsive and capable household robots.
Research Focus
Key Achievements
Top Papers
- 1