Motoyuki Suzuki
Papers
6
Total Citations
67
H-Index
4
About
Motoyuki Suzuki is a leading researcher in human-robot interaction, with a focus on enabling natural, robust communication between autonomous robots and humans. His work spans speech processing, emotion recognition, and context-aware robotic systems. Suzuki’s most influential contribution is his 2005 paper on internal noise suppression for small robots, which introduced novel spectral subtraction methods to overcome the challenge of a robot’s own mechanical noise interfering with speech recognition—a foundational issue in the field, with 41 citations. He further advanced spoken dialog systems by developing an automatic grammar generation and template-based weighting approach (2004, 8 citations), reducing the need for manual scripting. In emotion recognition, Suzuki pioneered methods for judging emotion from colloquial expressions using knowledge bases and association mechanisms (2014, 6 citations), as well as normalizing prosodic features for more accurate emotion detection (2013, 5 citations). His applied work includes a cooking support system integrating networked robots and sensors (2014, 4 citations), and a spokesperson detection method for complex communication environments (2010, 3 citations). Suzuki’s research is notable for bridging technical challenges in speech and emotion processing with practical robotic applications, making him a key figure in developing socially aware autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Internal noise suppression for speech recognition by small robots41 citations · 2005
- 2
- 3
- 4Emotion recognition method based on normalization of prosodic features5 citations · 2013
- 5Cooking Support System Using Networked Robots and Sensors4 citations · 2014
- 6