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Access. Comput."],"published-print":{"date-parts":[[2022,9,30]]},"abstract":"<jats:p>Navigating unfamiliar websites is challenging for users with visual impairments. Although many websites offer visual cues to facilitate access to pages\/features most websites are expected to have (e.g., log in at the top right), such visual shortcuts are not accessible to users with visual impairments. Moreover, although such pages serve the same functionality across websites (e.g., to log in, to sign up), the location, wording, and navigation path of links to these pages vary from one website to another. Such inconsistencies are challenging for users with visual impairments, especially for users of screen readers, who often need to linearly listen to content of pages to figure out how to access certain website features. To study how to improve access to main website features, we iteratively designed and tested a command-based approach for main features of websites via a browser extension powered by machine learning and human input. The browser extension gives users a way to access high-level website features (e.g., log in, find stores, contact) via keyboard commands. We tested the browser extension in a lab setting with 15 Internet users, including 9 users with visual impairments and 6 without. Our study showed that commands for main website features can greatly improve the experience of users with visual impairments. People without visual impairments also found command-based access helpful when visiting unfamiliar, cluttered, or infrequently visited websites, suggesting that this approach can support users with visual impairments while also benefiting other user groups (i.e., universal design). Our study reveals concerns about the handling of unsupported commands and the availability and trustworthiness of human input. 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