Papers
1
Total Citations
100
H-Index
1
About
Yung-Hwan Oh is a leading researcher in speech emotion recognition (SER) and human-robot interaction, with a particular focus on enabling service robots to understand and respond to human emotions. His most cited work, "Feature vector classification based speech emotion recognition for service robots" (2009, 100 citations), tackles the critical challenge of distinguishing between acoustically similar emotional states—a key barrier to natural human-robot communication. By proposing an efficient feature vector classification method, Oh’s research has directly advanced the ability of service robots to interact appropriately with users in diverse emotional conditions. This contribution is foundational for creating more empathetic and context-aware robotic systems. Oh’s work sits at the intersection of affective computing and robotics, demonstrating how robust SER can enhance user experience and safety in real-world applications. His findings remain highly influential, providing a practical framework for engineers and researchers developing emotionally intelligent machines. Through this impactful study, Oh has helped shape the trajectory of speech-based emotion analysis in robotics, making him a notable figure in the field.
Research Focus
Key Achievements
Top Papers
- 1