Multimodality, Context and Continuous Emotional Dynamics for Recognition and Synthesis

Learn about multimodal approaches to emotion recognition through this seminar that explores how context and continuous emotional dynamics can improve computational understanding of human emotions. Discover techniques for integrating multiple modalities including speech, facial expressions, and physiological signals to create more robust emotion recognition systems. Examine the role of temporal context in emotional state transitions and understand how continuous rather than discrete emotional models can better capture the nuanced nature of human emotional expression. Explore practical applications in human-computer interaction, affective computing, and psychological research while gaining insights into the challenges of modeling complex emotional phenomena across different communication channels.