Participation Role-Driven Engagement Estimation of ASD Individuals in Neurodiverse Group Discussions

Adults with autism spectrum disorder (ASD) face difculties in communicating with neurotypical people in their daily lives and workplaces. In addition, research on modeling communication in neurodiverse groups is scarce. To recognize communication difculties caused by neurodiversity, we frst, collected a multimodal corpus for decision-making discussions in neurodiverse groups that included a person with ASD and two neurotypical participants. For corpus analysis, we investigated eye-gaze and facial expression exchanges between individuals with ASD and neurotypical participants during both listening and speaking. The fndings were extended to automatically estimate the engagement of ASD individuals. To capture the efect of contingent behaviors between ASD individuals and neurotypical participants, we developed a transformer-based model that considers the participation role by changing the direction of cross-person attention depending on whether the ASD individual is listening or speaking. The proposed approach yields comparable results to the state-of-the-art for engagement estimation in neurotypical group conversations while accounting for the dynamic nature of behavior infuence in face-to-face interactions. The code associated with this study is available at https://github.com/IUI-Lab/switch-attention.