Multimodal Communication

Multimodal communication research focuses on understanding and replicating how humans integrate multiple communication channels (speech, gestures, facial expressions, etc.) for richer interaction. Current research emphasizes developing models, often employing transformer networks and graph convolutional networks, to detect and interpret these multimodal signals in various contexts, including human-robot interaction and conversational agents. This work is crucial for improving the naturalness and effectiveness of human-computer interaction, leading to more intuitive and empathetic AI systems and a deeper understanding of human communication itself.