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The majority of scientific papers are distributed in PDF, which posechallenges for accessibility, especially for blind and low vision (BLV)readers. We characterize the scope of this problem by assessing theaccessibility of 11,397 PDFs published 2010--2019 sampled across various fieldsof study, finding that only 2.4% of these PDFs satisfy all of our definedaccessibility criteria. We introduce the SciA11y system to offset some of theissues around inaccessibility. SciA11y incorporates several machine learningmodels to extract the content of scientific PDFs and render this content asaccessible HTML, with added novel navigational features to support screenreader users. An intrinsic evaluation of extraction quality indicates that themajority of HTML renders (87%) produced by our system have no or only somereadability issues. We perform a qualitative user study to understand the needsof BLV researchers when reading papers, and to assess whether the SciA11ysystem could address these needs. We summarize our user study findings into aset of five design recommendations for accessible scientific reader systems.User response to SciA11y was positive, with all users saying they would belikely to use the system in the future, and some stating that the system, ifavailable, would become their primary workflow. We successfully produce HTMLrenders for over 12M papers, of which an open access subset of 1.5M areavailable for browsing at https://scia11y.org/

Improving the Accessibility of Scientific Documents: Current State, User  Needs, and a System Solution to Enhance Scientific PDF Accessibility for  Blind and Low Vision Users