2 papers
eess.AS2025
Multimodal Fusion with Semi-Supervised Learning Minimizes Annotation Quantity for Modeling Videoconference Conversation Experience
Andrew Chang, Chenkai Hu, Ji Qi +5
Group conversations over videoconferencing are a complex social behavior. However, the subjective moments of negative experience, where the conversation loses fluidity or enjoyment…
cs.LG2025
Multimodal Machine Learning Can Predict Videoconference Fluidity and Enjoyment
Andrew Chang, Viswadruth Akkaraju, Ray McFadden Cogliano +2
Videoconferencing is now a frequent mode of communication in both professional and informal settings, yet it often lacks the fluidity and enjoyment of in-person conversation. This…