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Emotions play a key role in human-computer interaction. They are generally expressed through several ways (e.g. facial expressions, speech, body postures and gestures, etc). In this paper, we present a multimodal approach for the emotion recognition that integrates information coming from different cues and modalities. It is based on a formal multidimensional model using an algebraic representation...
Depression is a growing problem in our society. It causes pain and suffering not only to patients but also to those who care about them. This paper presents a multimodal emotion recognition system that is capable of preventing depression. It consists of detecting persistent negative emotions for early detection of depression. Our proposal is based on an algebraic representation of emotional states...
In this paper, we present a multimodal approach for the emotion recognition that takes into account more sources of information (physiological signals, facial expressions, speech, etc). This approach is based on an algebraic representation of emotional states using multidimensional vectors. This multidimensional model provides a powerful mathematical tools for the analysis and the processing of emotions...
In this study, we present a new vision of modeling emotional states. Indeed, the proposed model is different from traditional approaches like ontological representation. It is based on an algebraic representation of emotions. We represent every emotion as a vector in a space of 8 dimensions where every axis represents a basic emotion. This multidimensional model provides to represent infinity of emotion...
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