Group Conversation

Research on group conversation focuses on understanding and facilitating effective communication dynamics in multi-person interactions, aiming to improve both human-human and human-robot communication. Current studies employ various techniques, including deep learning models like LSTMs and Transformers, to analyze conversational patterns, predict speaker turns, and detect group formations from multimodal data (audio, video, text). This research is significant for advancing human-computer interaction, particularly in applications like assistive robotics for the elderly and improving the efficiency and inclusivity of global team collaborations.