Emotion Detection

Emotion detection research aims to automatically identify and categorize human emotions from various data sources, including text, speech, facial expressions, and physiological signals. Current research focuses on improving accuracy and efficiency using advanced techniques like transformer-based models, multimodal fusion methods, and personalized AI models tailored to specific user groups or contexts. This field is significant for its potential applications in diverse areas such as mental health monitoring, human-computer interaction, and social media analysis, offering valuable insights into human behavior and improving the design of technology that interacts with people.