A Literature Survey On Multi-modal Emotion Detection System

Emotion recognition has garnered significant attention due to its potential applications across various domains such as healthcare, education, and human-computer interaction. This paper presents a multimodal emotion recognition system that combines facial expression analysis and text sentiment analysis to improve the accuracy and effectiveness of emotion detection. Utilizing deep learning techniques, such as Convolutional Neural Networks (CNNs) for facial expression recognition and Natural Language Processing (NLP) for text sentiment analysis, this system can classify emotions in real-time. The paper provides a comprehensive overview of the system's design, the models used, and the challenges faced in the development process, including data integration and real-time processing. Through this work, we demonstrate how multimodal approaches can significantly enhance emotion detection accuracy in a variety of settings.