Attention and Engagement Aware Multimodal Conversational Systems

Abstract

Despite their ability to complete certain tasks, dialog systems still suffer from poor adaptation to users' engagement and attention. We observe human behaviors in different conversational settings to understand human communication dynamics and then transfer the knowledge to multimodal dialog system design. To focus solely on maintaining engaging conversations, we design and implement a non-task oriented multimodal dialog system, which serves as a framework for controlled multimodal conversation analysis. We design computational methods to model user engagement and attention in real time by leveraging automatically harvested multimodal human behaviors, such as smiles and speech volume. We aim to design and implement a multimodal dialog system to coordinate with users' engagement and attention on the fly via techniques such as adaptive conversational strategies and incremental speech production.