Emotion Discovery

Emotion discovery research focuses on automatically identifying and understanding human emotions from various data sources, such as text, speech, facial expressions, physiological signals, and brain activity. Current research heavily utilizes deep learning models, including transformers, LSTMs, and variational autoencoders, often incorporating multimodal data fusion techniques to improve accuracy and contextual understanding. This field is significant for advancing human-computer interaction, mental health applications, and the development of more empathetic and socially intelligent AI systems.