4 papers
VIP-MINGLE: A Corpus for Videoconference and In-Person Multimodal Interaction in Group Language Engagement
Andrew Chang, Abhinay K Bodi, Wenxin Deng +6
Group conversations are a fundamental yet complex form of social interaction central to human cognition and telecommunication technology. While understanding and facilitating these…
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…
Spectrotemporal Modulation: Efficient and Interpretable Feature Representation for Classifying Speech, Music, and Environmental Sounds
Andrew Chang, Yike Li, Iran R. Roman +1
Audio DNNs have demonstrated impressive performance on various machine listening tasks; however, most of their representations are computationally costly and uninterpretable, leavi…
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…