One to One

One-to-one interactions, encompassing both human-human and human-computer communication, are a central focus of current research, aiming to understand and model the complex dynamics within these exchanges. Studies are exploring diverse modalities, including facial expressions, body language, and speech, employing machine learning techniques like self-supervised pre-training and adversarial learning to improve model accuracy and mitigate biases (e.g., age effects). This research is significant for advancing human-computer interaction, enabling applications such as improved hearing aid technology and more socially intelligent robots, while also furthering our understanding of human behavior and communication.