Papers
9
Total Citations
186
H-Index
6
About
Marie Tahon is a leading researcher in affective computing and human-robot interaction (HRI), with a focus on emotion recognition from speech. Her work addresses the critical challenge of developing robust acoustic feature sets that can reliably detect human emotional states in real-world, noisy environments—a key bottleneck for deploying socially intelligent robots. Her most cited paper (96 citations) systematically tackles the difficulties of creating a small, robust set of acoustic features for emotion recognition, emphasizing the need for context-robustness and optimized model parameters. Tahon’s impact is evident in her pioneering cross-corpus experiments, which validate emotion and laughter detection across diverse populations—from children interacting with the Nao robot to elderly users in HRI settings. She has been instrumental in the Romeo2 Project, developing situation assessment for social intelligence in humanoid assistants. Her work on Wizard-of-Oz protocols for collecting emotional audio data from children, and her creation of a children’s voice corpus for affect burst analysis, have provided foundational resources for the field. By bridging acoustic analysis with real-life HRI applications, Tahon’s research directly advances the goal of creating empathetic, responsive robotic companions.
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- 9Laughter Detection For On-Line Human-Robot Interaction2 citations · 2015