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Deep Learning Methods for Modelling Emotional Intelligence
Abstract
Machine learning and deep learning play a vital role in making smart decisions, especially with huge amounts of data. Identifying the emotional intelligence levels of individuals helps them to avoid superfluous problems in the workplace or in society. Emotions reflect the psychological state of a person or represent a quick (a few minutes or seconds) reactions to a stimulus. Emotions can be categorized on the basis of a person's feelings in a situation: positive, negative, and neutral. Emotional intelligence seeks attention from computer engineers and psychologists to work together to address EI. However, identifying human emotions through deep learning methods is still a challenging task in computer vision. This chapter investigates deep learning models for the recognition and assessment of emotional states with diverse emotional data such as speech and video streaming. Finally, the conclusion summarises the usefulness of DL methods in assessing human emotions. It helps future researchers carry out their work in the field of deep learning-based emotional artificial intelligence.
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