Lasecki, Walter S. Thiha, Phyo Zhong, Yu Brady, Erin Bigham, Jeffrey P. Answering Visual Questions with Conversational Crowd Assistants <p>Blind people face a range of accessibility challenges in their everyday lives, from reading the text on a package of food to traveling independently in a new place. Answering general questions about one’s visual surroundings remains well beyond the capabilities of fully automated systems, but recent systems are showing the potential of engaging on-demand human workers (the crowd) to answer visual questions. The input to such systems has generally been a single image, which can limit the interaction with a worker to one question; or video streams where systems have paired the end user with a single worker, limiting the benefits of the crowd. In this paper, we introduce Chorus:View, a system that assists users over the course of longer interactions by engaging workers in a continuous conversation with the user about a video stream from the user’s mobile device. We demonstrate the benefit of using multiple crowd workers instead of just one in terms of both latency and accuracy, then conduct a study with 10 blind users that shows Chorus:View answers common visual questions more quickly and accurately than existing approaches. We conclude with a discussion of users’ feedback and potential future work on interactive crowd support of blind users</p> Assistive Technology;Crowdsourcing;Human Computation 2013-09-01
    https://kilthub.cmu.edu/articles/journal_contribution/Answering_Visual_Questions_with_Conversational_Crowd_Assistants/6469823
10.1184/R1/6469823.v1