Online shopping has become a valuable modern convenience, but blind or low vision (BLV) users still face significant challenges using it, because of: 1) inadequate image descriptions and 2) the inability to filter large amounts of information using screen readers. To address those challenges, we propose Revamp, a system that leverages customer reviews for interactive information retrieval. Revamp is a browser integration that supports review-based question-answering interactions on a reconstructed product page. From our interview, we identified four main aspects (color, logo, shape, and size) that are vital for BLV users to understand the visual appearance of a product. Based on the findings, we formulated syntactic rules to extract review snippets, which were used to generate image descriptions and responses to users' queries. Evaluations with eight BLV users showed that Revamp 1) provided useful descriptive information for understanding product appearance and 2) helped the participants locate key information efficiently.
翻译:在线购物已成为一个宝贵的现代便利,但盲目或低视点用户仍面临重大挑战,因为:(1) 图像描述不足,(2) 无法利用屏幕阅读器过滤大量信息。为应对这些挑战,我们提议了 " Revamp ",这是一个利用客户审查来交互检索信息的系统。 " Revamp " 是一个浏览器整合,支持在重建的产品页面上基于审查的问答互动。我们从访谈中发现四个主要方面(颜色、标志、形状和大小),对于BLV用户理解产品视觉外观至关重要。根据调查结果,我们制定了综合规则来提取审查片段,用于生成图像描述和用户询问的答案。与8个 " Revamp " 用户进行的评价表明, " Revamp 1 " 提供了了解产品外观和2的有用描述信息,帮助与会者有效地找到了关键信息。