Manuel Milling
Papers
3
Total Citations
31
H-Index
2
About
Manuel Milling is a researcher at the intersection of affective computing, assistive robotics, and neurodevelopmental disorders, with a primary focus on automatic emotion recognition for children with Autism Spectrum Disorder (ASD). His work addresses a critical challenge: how to reliably observe and interpret the affective states of autistic children during human-robot interaction. Milling’s most cited paper (21 citations) evaluates the impact of Voice Activity Detection on speech emotion recognition for autistic children, highlighting the technical nuances of processing non-typical vocal expressions. He further investigates the methodological challenges of multi-modal data acquisition in observing emotions during interactions with the social robot Kaspar, as detailed in his 2024 work (8 citations). His research is grounded in the European Commission’s Erasmus Plus project “EMBOA,” which aims to create an affective loop in socially assistive robotics. By pioneering robust speech and behavioral analysis techniques, Milling is helping to make robot-assisted therapy more responsive and effective for children with ASD, contributing to a future where technology can better understand and support diverse emotional expressions.
Research Focus
Key Achievements
Top Papers
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