Towards Semantic Multimodal Emotion Recognition for Enhancing Assistive Services in Ubiquitous Robotics
Résumé
In this paper, the problem of endowing ubiquitous robots with
cognitive capabilities for recognizing emotions, sentiments,
affects and moods of humans, in their context, is studied. A
hybrid approach based on multilayer perceptron (MLP) neural network and n-ary ontologies for emotion-aware robotic
systems is proposed. In particular, an algorithm based on the
hybrid-level fusion, an expressive emotional knowledge representation and reasoning model are introduced to recognize
complex and non-observable emotional context of the user.
Empirical experiments on real-world dataset corroborate its
effectiveness.