Discrete Emotion

Discrete emotion research aims to computationally model and recognize distinct emotional states from various modalities like text, speech, and images. Current research focuses on addressing the ambiguity inherent in human emotion, often employing transformer-based models, and exploring both discrete emotion categories and continuous dimensional representations (e.g., valence and arousal) to achieve more nuanced and accurate emotion understanding. This work has significant implications for improving human-computer interaction, particularly in developing more empathetic and responsive AI systems, as well as advancing our understanding of human emotion itself.