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Main Authors: Schmitt-Koopmann, Felix M., Huang, Elaine M., Hutter, Hans-Peter, Darvishy, Alireza
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2503.22216
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author Schmitt-Koopmann, Felix M.
Huang, Elaine M.
Hutter, Hans-Peter
Darvishy, Alireza
author_facet Schmitt-Koopmann, Felix M.
Huang, Elaine M.
Hutter, Hans-Peter
Darvishy, Alireza
contents PDF inaccessibility is an ongoing challenge that hinders individuals with visual impairments from reading and navigating PDFs using screen readers. This paper presents a step-by-step process for both novice and experienced users to create accessible PDF documents, including an approach for creating alternative text for mathematical formulas without expert knowledge. In a study involving nineteen participants, we evaluated our prototype PAVE 2.0 by comparing it against Adobe Acrobat Pro, the existing standard for remediating PDFs. Our study shows that experienced users improved their tagging scores from 42.0% to 80.1%, and novice users from 39.2% to 75.2% with PAVE 2.0. Overall, fifteen participants stated that they would prefer to use PAVE 2.0 in the future, and all participants would recommend it for novice users. Our work demonstrates PAVE 2.0's potential for increasing PDF accessibility for people with visual impairments and highlights remaining challenges.
format Preprint
id arxiv_https___arxiv_org_abs_2503_22216
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Towards More Accessible Scientific PDFs for People with Visual Impairments: Step-by-Step PDF Remediation to Improve Tag Accuracy
Schmitt-Koopmann, Felix M.
Huang, Elaine M.
Hutter, Hans-Peter
Darvishy, Alireza
Human-Computer Interaction
PDF inaccessibility is an ongoing challenge that hinders individuals with visual impairments from reading and navigating PDFs using screen readers. This paper presents a step-by-step process for both novice and experienced users to create accessible PDF documents, including an approach for creating alternative text for mathematical formulas without expert knowledge. In a study involving nineteen participants, we evaluated our prototype PAVE 2.0 by comparing it against Adobe Acrobat Pro, the existing standard for remediating PDFs. Our study shows that experienced users improved their tagging scores from 42.0% to 80.1%, and novice users from 39.2% to 75.2% with PAVE 2.0. Overall, fifteen participants stated that they would prefer to use PAVE 2.0 in the future, and all participants would recommend it for novice users. Our work demonstrates PAVE 2.0's potential for increasing PDF accessibility for people with visual impairments and highlights remaining challenges.
title Towards More Accessible Scientific PDFs for People with Visual Impairments: Step-by-Step PDF Remediation to Improve Tag Accuracy
topic Human-Computer Interaction
url https://arxiv.org/abs/2503.22216