Poster: A Theory -Informed Roadmap Towards Multimodal Ocular-based Attention Metrics for Conversational VR

Eye- tracking in consumer head-mounted displays (HMDs) already provides reliable data for visual attention tracking. We now strive to extend this capability to conversational attention, which also involves auditory processing, cognitive load, mind-wandering, and fatigue. To this end, we propose a taxonomy that maps gaze, blink dynamics, and pupillometry onto these five complementary dimensions and briefly summarize current eye - tracking- based evaluation methods. From the identified gaps, we outline a three - stage research roadmap — (i) robust pupillometry calibration, (ii) multimodal signal disambiguation, and (iii) composite attention-score fusion — aimed at achieving reliable, real -time inference of attentional engagement in Virtual-Reality (VR)-based dialogues.