Answering visual questions with conversational crowd assistants

Abstract

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.

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