Antoine Raux
Papers
7
Total Citations
76
H-Index
5
About
Antoine Raux is a leading researcher in situated language understanding and human-robot interaction, whose work has fundamentally shaped how machines communicate in dynamic, real-world environments. His research focuses on developing spoken dialogue systems that operate effectively in rapidly changing contexts, particularly within moving vehicles and robotic platforms. Raux’s most influential contribution is his pioneering approach to situated language understanding at high speeds, as demonstrated in his landmark paper “Situated Language Understanding at 25 Miles per Hour” (2014, 19 citations), where he proposed novel methods for interpreting user queries about specific target buildings from a moving car—a challenge that previous studies had not addressed. He also developed the Human-Robot Interaction Toolkit (HRItk, 2012, 10 citations), a widely used framework for building speech-centric interactive systems within ROS, significantly lowering the barrier for integrating spoken dialogue into robotics. His work on action corrections in situated interaction (2010, 7 citations) advanced automatic detection of correction utterances, a key component for fluid human-robot communication. As co-editor of special issues on Dialogue with Robots (2011) and Machine Learning for Multiple Modalities (2014), Raux has helped define the research agenda for multimodal, situated dialogue systems, leaving a lasting impact on both academic research and practical deployment.
Research Focus
Key Achievements
Top Papers
- 1Dialog with robots : papers from the AAAI Fall Symposium20 citations · 2010
- 2Situated Language Understanding at 25 Miles per Hour19 citations · 2014
- 3Situated language understanding for a spoken dialog system within vehicles12 citations · 2015
- 4HRItk: The Human-Robot Interaction ToolKit Rapid Development of Speech-Centric Interactive Systems in ROS10 citations · 2012
- 5The Dynamics of Action Corrections in Situated Interaction7 citations · 2010
- 6Introduction to the Special Issue on Dialogue with Robots4 citations · 2011
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