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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.08582 |
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| _version_ | 1866911102331256832 |
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| author | wang, Ruolin Liu, Xingyu Wang, Biao Zhang, Wayne Liao, Ziqian Li, Ziwen Pavel, Amy Chen, Xiang 'Anthony' |
| author_facet | wang, Ruolin Liu, Xingyu Wang, Biao Zhang, Wayne Liao, Ziqian Li, Ziwen Pavel, Amy Chen, Xiang 'Anthony' |
| contents | The rapid growth of online video content has outpaced efforts to make visual information accessible to blind and low vision (BLV) audiences. While professional Audio Description (AD) remains the gold standard, it is costly and difficult to scale across the vast volume of online media. In this work, we explore a complementary approach to broaden participation in video accessibility: engaging everyday video viewers at their watching and commenting time. We introduce CoSight, a Chrome extension that augments YouTube with lightweight, in-situ nudges to support descriptive commenting. Drawing from Fogg's Behavior Model, CoSight provides visual indicators of accessibility gaps, pop-up hints for what to describe, reminders to clarify vague comments, and related captions and comments as references. In an exploratory study with 48 sighted users, CoSight helped integrate accessibility contribution into natural viewing and commenting practices, resulting in 89% of comments including grounded visual descriptions. Follow-up interviews with four BLV viewers and four professional AD writers suggest that while such comments do not match the rigor of professional AD, they can offer complementary value by conveying visual context and emotional nuance for understanding the videos. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_08582 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | CoSight: Exploring Viewer Contributions to Online Video Accessibility Through Descriptive Commenting wang, Ruolin Liu, Xingyu Wang, Biao Zhang, Wayne Liao, Ziqian Li, Ziwen Pavel, Amy Chen, Xiang 'Anthony' Human-Computer Interaction K.4.2 The rapid growth of online video content has outpaced efforts to make visual information accessible to blind and low vision (BLV) audiences. While professional Audio Description (AD) remains the gold standard, it is costly and difficult to scale across the vast volume of online media. In this work, we explore a complementary approach to broaden participation in video accessibility: engaging everyday video viewers at their watching and commenting time. We introduce CoSight, a Chrome extension that augments YouTube with lightweight, in-situ nudges to support descriptive commenting. Drawing from Fogg's Behavior Model, CoSight provides visual indicators of accessibility gaps, pop-up hints for what to describe, reminders to clarify vague comments, and related captions and comments as references. In an exploratory study with 48 sighted users, CoSight helped integrate accessibility contribution into natural viewing and commenting practices, resulting in 89% of comments including grounded visual descriptions. Follow-up interviews with four BLV viewers and four professional AD writers suggest that while such comments do not match the rigor of professional AD, they can offer complementary value by conveying visual context and emotional nuance for understanding the videos. |
| title | CoSight: Exploring Viewer Contributions to Online Video Accessibility Through Descriptive Commenting |
| topic | Human-Computer Interaction K.4.2 |
| url | https://arxiv.org/abs/2508.08582 |