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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-25873
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dc.contributor.authorSchmitt-Koopmann, Felix M.-
dc.contributor.authorHuang, Elaine M.-
dc.contributor.authorDarvishy, Alireza-
dc.date.accessioned2022-10-28T12:26:17Z-
dc.date.available2022-10-28T12:26:17Z-
dc.date.issued2022-
dc.identifier.isbn978-1-4503-9258-7de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/25873-
dc.description.abstractPeople with visual impairments use assistive technology, e.g., screen readers, to navigate and read PDFs. However, such screen readers need extra information about the logical structure of the PDF, such as the reading order, header levels, and mathematical formulas, described in readable form to navigate the document in a meaningful way. This logical structure can be added to a PDF with tags. Creating tags for a PDF is time-consuming, and requires awareness and expert knowledge. Hence, most PDFs are left untagged, and as a result, they are poorly readable or unreadable for people who rely on screen readers. STEM documents are particularly problematic with their complex document structure and complicated mathematical formulae. These inaccessible PDFs present a major barrier for people with visual impairments wishing to pursue studies or careers in STEM fields, who cannot easily read studies and publications from their field. The goal of this Ph.D. is to apply artificial intelligence for document analysis to reasonably automate the remediation process of PDFs and present a solution for large mathematical formulae accessibility in PDFs. With these new methods, the Ph.D. research aims to lower barriers to creating accessible scientific PDFs, by reducing the time, effort, and expertise necessary to do so, ultimately facilitating greater access to scientific documents for people with visual impairments.de_CH
dc.language.isoende_CH
dc.publisherAssociation for Computing Machineryde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectAccessibilityde_CH
dc.subjectPDF accessibilityde_CH
dc.subjectTagged PDFde_CH
dc.subjectPDF/UAde_CH
dc.subjectMath viewerde_CH
dc.subjectDocument analysisde_CH
dc.subjectFormula recognitionde_CH
dc.subjectPage object detectionde_CH
dc.subjectReading orderde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleAccessible PDFs : applying artificial intelligence for automated remediation of STEM PDFsde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.1145/3517428.3550407de_CH
dc.identifier.doi10.21256/zhaw-25873-
zhaw.conference.details24th International ACM SIGACCESS Conference on Computers and Accessibility, Athens, Greece, 23-26 October 2022de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.start90de_CH
zhaw.parentwork.editorFroehlich, Jon-
zhaw.parentwork.editorShinohara, Kristen-
zhaw.parentwork.editorLudi, Stephanie-
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsASSETS '22 Proceedingsde_CH
zhaw.webfeedHuman Information Interactionde_CH
zhaw.webfeedHuman-Centered Computingde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Schmitt-Koopmann, F. M., Huang, E. M., & Darvishy, A. (2022). Accessible PDFs : applying artificial intelligence for automated remediation of STEM PDFs [Conference paper]. In J. Froehlich, K. Shinohara, & S. Ludi (Eds.), ASSETS ’22 Proceedings (p. 90). Association for Computing Machinery. https://doi.org/10.1145/3517428.3550407
Schmitt-Koopmann, F.M., Huang, E.M. and Darvishy, A. (2022) ‘Accessible PDFs : applying artificial intelligence for automated remediation of STEM PDFs’, in J. Froehlich, K. Shinohara, and S. Ludi (eds) ASSETS ’22 Proceedings. Association for Computing Machinery, p. 90. Available at: https://doi.org/10.1145/3517428.3550407.
F. M. Schmitt-Koopmann, E. M. Huang, and A. Darvishy, “Accessible PDFs : applying artificial intelligence for automated remediation of STEM PDFs,” in ASSETS ’22 Proceedings, 2022, p. 90. doi: 10.1145/3517428.3550407.
SCHMITT-KOOPMANN, Felix M., Elaine M. HUANG und Alireza DARVISHY, 2022. Accessible PDFs : applying artificial intelligence for automated remediation of STEM PDFs. In: Jon FROEHLICH, Kristen SHINOHARA und Stephanie LUDI (Hrsg.), ASSETS ’22 Proceedings. Conference paper. Association for Computing Machinery. 2022. S. 90. ISBN 978-1-4503-9258-7
Schmitt-Koopmann, Felix M., Elaine M. Huang, and Alireza Darvishy. 2022. “Accessible PDFs : Applying Artificial Intelligence for Automated Remediation of STEM PDFs.” Conference paper. In ASSETS ’22 Proceedings, edited by Jon Froehlich, Kristen Shinohara, and Stephanie Ludi, 90. Association for Computing Machinery. https://doi.org/10.1145/3517428.3550407.
Schmitt-Koopmann, Felix M., et al. “Accessible PDFs : Applying Artificial Intelligence for Automated Remediation of STEM PDFs.” ASSETS ’22 Proceedings, edited by Jon Froehlich et al., Association for Computing Machinery, 2022, p. 90, https://doi.org/10.1145/3517428.3550407.


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