Rule Based System for Recognizing Emotions Using Multimodal Approach

Abstract

Abstract-Emotion is assuming increasing importance in human computer interaction (HCI), in general, with the growing feeling that emotion is central to human communication and intelligence. Users expect not just functionality as a factor of usability, but experiences, matched to their expectations, emotional states, and interaction goals. Endowing computers with this kind of intelligence for HCI is a complex task. It becomes more complex with the fact that the interaction of humans with their environment (including other humans) is naturally multimodal. In reality, one uses a combination of modalities and they are not treated independently. In an attempt to render HCI more similar to human-human communication and enhance its naturalness, research on multiple modalities of human expressions has seen ongoing progress in the past few years. As compared to unimodal approaches, various problems arise in case of multimodal emotion recognition especially concerning fusion architecture of multimodal information. In this paper we will be proposing a rule based hybrid approach to combine the information from various sources for recognizing the target emotions. The results presented in this paper shows that it is feasible to recognize human affective states with a reasonable accuracy by combining the modalities together using rule based system.

Prediction of Baby Emotions through Pattern Recognition by Monitoring Baby's Biological Measurements

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“…Uncertainty is inherently part of most human decision making. This uncertainty could arise from various sources like incomplete data or domain knowledge used being unreliable [12].…”

“…Khanna and Sasikumar (2013) [12], says to handle these uncertainties, there are two broad approachesthose representing uncertainty using numerical quantities and those using symbolic methods.…”

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