Xiao Yao
Papers
1
Total Citations
2
H-Index
1
About
Xiao Yao is a researcher whose work sits at the intersection of speech processing, human-robot interaction, and affective computing. Their primary focus is on understanding how physiological and cognitive states—particularly stress and workload—alter the acoustic properties of speech, with the goal of improving the reliability of human-robot interfaces. Yao’s most cited work, "Glottal source related to stressed speech under workload in human-robot interface" (2017), investigates how variations in the glottal source signal reflect speaker stress, a critical factor that degrades automatic speech recognition performance in real-world, high-pressure environments. This contribution highlights the challenge of achieving robust speech interfaces when users are under cognitive load. While their citation count is modest, the research addresses a fundamental bottleneck in human-robot communication: the mismatch between clean training data and noisy, stressed speech in the field. Yao’s work is notable for bridging phonetics and engineering, offering a pathway toward more adaptive and resilient voice-controlled systems.
Research Focus
Key Achievements
Top Papers
- 1