EMOTION AI: UNDERSTANDING EMOTIONS THROUGH ARTIFICIAL INTELLIGENCE
Keywords:
Emotion, Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP)Abstract
Emotion AI, also known as sentiment analysis or affective computing, refers to the ability of AI systems to recognize, analyze, and interpret human emotions through various inputs, such as text, speech, facial expressions, and physiological signals. With the recent advancements in artificial intelligence (AI) and machine learning, emotion analysis has witnessed significant progress in terms of accuracy, efficiency, and scalability. This paper provides an overview of the emotion analysis through AI, explores its applications and challenges that researchers and developers face in this domain, and showcases the potential applications of this technology.
References
Beck, M., & Libert, B. (2017). The rise of AI makes emotional intelligence more important. Harvard Business Review, 15(1-5).
Pfeifer, R. (1988). Artificial intelligence models of emotion. In Cognitive perspectives on emotion and motivation (pp. 287-320). Dordrecht: Springer Netherlands.
James, W. (2013). What is an Emotion?. Simon and Schuster.
Cornelius, R. R. (1996). Research and tradition in the psychology of emotion: The science of emotion.
Dollmat, K. S., & Abdullah, N. A. (2022). Machine learning in emotional intelligence studies: a survey. Behaviour& Information Technology, 41(7), 1485-1502.
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