Yuxing Gu
Papers
1
Total Citations
2
H-Index
1
About
Yuxing Gu’s research lies at the intersection of speech processing, human-robot interaction, and affective computing, with a particular focus on how cognitive and emotional states—such as stress and workload—alter speech production. Their most cited work, “Glottal source related to stressed speech under workload in human-robot interface” (2017), investigates how physiological stress from demanding tasks impacts the glottal source, the fundamental vibration of the vocal folds. By analyzing these subtle acoustic changes, Gu’s research addresses a critical barrier in human-robot interfaces: the degradation of speech recognition accuracy under real-world stress conditions. This contribution is vital for designing more robust, adaptive systems that can interpret human speech reliably even when speakers are under cognitive load. While their citation count is modest, the work’s focus on the underexplored glottal source offers a foundational perspective for improving voice-controlled interfaces in high-stakes environments like aviation, emergency response, or collaborative robotics. Gu’s research highlights the importance of integrating physiological and acoustic analysis to advance human-centered technology.
Research Focus
Key Achievements
Top Papers
- 1