Publication

Automatic Alt-text: Computer-generated Image Descriptions for Blind Users on a Social Network Service

CSCW


Abstract

We designed and deployed automatic alt-text (AAT), a system that applies computer vision technology to identify faces, objects, and themes from photos to generate photo alt-text for screen reader users on Facebook. We designed our system through iterations of prototyping and in-lab user studies. Our lab test participants had a positive reaction to our system and an enhanced experience with Facebook photos. We also evaluated our system through a two-week field study as part of the Facebook iOS app for 9K VoiceOver users. We randomly assigned them into control and test groups and collected two weeks of activity data and their survey feedback. The test group reported that photos on Facebook were easier to interpret and more engaging, and found Facebook more useful in general. Our system demonstrates that artificial intelligence can be used to enhance the experience for visually impaired users on social networking sites (SNSs), while also revealing the challenges with designing automated assistive technology in a SNS context.

Related Publications

All Publications

EMNLP - October 31, 2021

Evaluation Paradigms in Question Answering

Pedro Rodriguez, Jordan Boyd-Graber

ASRU - December 13, 2021

Incorporating Real-world Noisy Speech in Neural-network-based Speech Enhancement Systems

Yangyang Xia, Buye Xu, Anurag Kumar

IROS - September 1, 2021

Success Weighted by Completion Time: A Dynamics-Aware Evaluation Criteria for Embodied Navigation

Naoki Yokoyama, Sehoon Ha, Dhruv Batra

To help personalize content, tailor and measure ads, and provide a safer experience, we use cookies. By clicking or navigating the site, you agree to allow our collection of information on and off Facebook through cookies. Learn more, including about available controls: Cookies Policy