Alternative (alt) text provides access to descriptions of digital images for people who use screen readers. While prior work studied screen reader users\u2019 (SRUs\u2019) preferences about alt text and automatic alt text (i.e., alt text generated by artificial intelligence), little work examined the alt text author\u2019s experience composing or editing these descriptions. We built two types of prototype interfaces for two tasks: authoring alt text and providing feedback on automatic alt text. Through combined interview-usability testing sessions with alt text authors and interviews with SRUs, we tested the effectiveness of our prototypes in the context of Microsoft PowerPoint. Our results suggest that authoring interfaces that support authors in choosing what to include in their descriptions result in higher quality alt text. The feedback interfaces highlighted considerable differences in the perceptions of authors and SRUs regarding \u201chigh-quality\u201d alt text. Finally, authors crafted significantly lower quality alt text when starting from the automatic alt text compared to starting from a blank box. We discuss the implications of these results on applications that support alt text.<\/p>\n","protected":false},"excerpt":{"rendered":"
Alternative (alt) text provides access to descriptions of digital images for people who use screen readers. While prior work studied screen reader users\u2019 (SRUs\u2019) preferences about alt text and automatic alt text (i.e., alt text generated by artificial intelligence), little work examined the alt text author\u2019s experience composing or editing these descriptions. We built two 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