Papers
8
Total Citations
76
H-Index
5
About
Fabien Gouyon is a pioneering researcher at the intersection of robotics, music perception, and human-robot interaction, whose work has fundamentally shaped how machines understand and respond to musical rhythm. His primary research areas include auditory-driven human-robot interaction, beat tracking for robotic systems, and the computational modeling of dance movements. Gouyon's major contributions lie in developing frameworks that enable robots to listen to music in real-time, synchronize their movements to diverse musical genres, and interact with humans through dance—even in noisy, real-world environments. His most influential work, "Humanized Robot Dancing," has garnered 18 citations and introduced novel methods for retargeting human dance styles onto humanoid robots using metrical representations. Gouyon's active audition framework, cited 16 times, simultaneously processes speech and music on-the-fly, integrating perceptual models that support both verbal and nonverbal communication. He has also made significant advances in overcoming motor-rate limitations for online synchronized dancing, enabling low-cost humanoid robots to perform fluid, rhythmically accurate movements. Through his empirical evaluations and live beat tracking assessments, Gouyon has established foundational principles that continue to inspire robotic dance competitions and real-world applications in socially interactive robotics.
Research Focus
Key Achievements
Top Papers
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- 4Beat Tracking for Interactive Dancing Robots11 citations · 2015
- 5Live assessment of beat tracking for robot audition8 citations · 2012
- 6
- 7Overcoming Motor-Rate Limitations in Online Synchronized Robot Dancing4 citations · 2012
- 8Making a robot dance to diverse musical genre in noisy environments2 citations · 2014