Xuan Guo
Papers
2
Total Citations
15
H-Index
2
About
Xuan Guo is a researcher in the field of intelligent auditory perception, with a primary focus on environmental sound recognition for robotics and intelligent systems. Their major contribution lies in developing novel time-frequency intersection patterns as input features for neural network-based sound classification. By combining instantaneous power variations with spectral information into a one-dimensional representation, Guo created an efficient method for machines to interpret complex acoustic environments. This work, published in 2011 and 2012, has accumulated a combined 15 citations, establishing a foundation for subsequent research in acoustic scene analysis. Guo’s approach demonstrates how multi-stage perceptron neural networks can effectively process environmental sounds, enabling robots and computers to better understand their surroundings. This research is particularly valuable for applications in autonomous navigation, smart home systems, and human-robot interaction, where accurate sound recognition is crucial for context-aware decision-making.
Research Focus
Key Achievements
Top Papers
- 1Environmental Sound Recognition Using Time-Frequency Intersection Patterns11 citations · 2012
- 2