Effects of Crowd-in-the-loop Alt Text Addition on the Performance of Visually Impaired Workers in Online Microtasks

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Microtasks, which are tasks that can be performed online in a short period of time, have been attracting a lot of attention as a new form of work. Some online microtasks require workers to look at web pages with images. Therefore, if visually impaired people want to work on such tasks, they have to rely on alt texts attached to images on web pages to complete their online tasks. However, too many alt texts of the unrelated images may increase the difficulty of reading. This paper proposes a crowd-in-the-loop alt text addition method for online microtasks. The proposed method combines AI and crowdsourcing to add alt texts on only important images. To check how the proposed method contributes to the real world, we conducted an experiment involving 18 sighted participants (simulated visually impaired participants) and 4 visually impaired participants. In our experiment, we compare three conditions, specifically, conditions involving (1) no alt text, (2) only important images with alt text, and (3) all images with alt text in online microtasks. Workers are often required to look at other Web pages than the task instruction page to complete the tasks, such as shopping and social networking websites. Twelve tasks pertaining to 4 fake web pages were designed as the experiment tasks. We observed that the situation involving only important images with alt text could facilitate the workers’ understanding, and the worker performance in this condition was better than that in the other conditions. The proposed method is expected to improve the performance of visually impaired workers in online microtasks.

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