EMotion Share

Emotion sharing research focuses on understanding and modeling how emotions are communicated and perceived, particularly through speech and text. Current efforts leverage large language models and deep learning architectures, such as self-attention networks and pre-trained models like HuBERT, to analyze and generate emotional expressions, improve emotion classification accuracy, and even design interactive systems like chatbots that facilitate emotional communication, especially with children. This work is significant for advancing human-computer interaction, improving mental health support technologies, and furthering our understanding of the complex interplay between language, emotion, and perception.