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To help people improve their reading of faces during natural conversations, we developed a video tool to evaluate this skill. We collected over 100 videos of conversations between pairs of both autistic and neurotypical people, each wearing a Self-Cam. The videos were manually segmented into chunks of 7-20 seconds according to expressive content, labeled, and sorted by difficulty—all tasks we plan to automate using technologies under development. Next, we built a rating interface including videos of self, peers, familiar adults, strangers, and unknown actors, allowing for performance comparisons across conditions of familiarity and expression. We obtained reliable identification (by coders) of categories of smiling, happy, interested, thinking, and unsure in the segmented videos. The tool was finally used to assess recognition of these five categories for eight neurotypical and five autistic people. Results show some autistics approaching the abilities of neurotypicals while several score just above random.