Title: When digital feels human: Investigating dialogue naturalness with multivariate neural data
Description: The interaction with digital systems has become a pervasive daily experience (e.g., video-calls, dialogue systems). One major barrier remains that users need to adapt the way they communicate to each particular digital system, for example constituting a challenge for inclusivity. This project will identify objective indices that quantify the naturalness of a conversation by using bio-signals recorded with electroencephalography and pupillometry. These metrics will inform us on how exactly different digital communication strategies (e.g., video-call software) impact cognition (e.g., cognitive load, phonological processing, temporal expectations). In doing so, this project will inform us on the key elements for producing adaptive dialogue systems.