Modeling Human Communication Dynamics

Face-to-face communication is a highly dynamic process where participants mutually exchange and interpret linguistic and gestural signals. The goal of this project is to create a new generation of computational models to learn the interdependence between linguistic symbols and nonverbal signals during social interactions. Our computational framework will pave the way for new robust and efficient computational perception algorithms able to recognize high-level communicative behaviors (e.g., intent and sentiments) and will enable new computational tools for researchers in behavioral sciences.