liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Auxiliary Techniques to Help Readers Understand Texts
Linköping University, Department of Computer and Information Science, Human-Centered Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Human-Centered Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-4899-588X
2024 (English)In: Papers from The Tenth Swedish Language Technology Conference (SLTC), 2024Conference paper, Published paper (Other academic)
Abstract [en]

 We explore three auxiliary techniques for automatic text adaptation (ATA)—epithets for nouns, explanations for keywords, and syllabification—to aid reading for individuals with reading difficulties. In an initial evaluation, we conducted a study with individuals possessing average reading skills. Results indicate that while all three techniques demonstrate high accuracy, their usefulness varies. Epithets were found to be less beneficial, possibly due to the introduction of excessive information, although they may assist certain populations, such as individuals with intellectual disabilities. Keyword explanations were generally helpful and accurate, though occasional inaccuracies arose with rare or domain-specific terms. The effectiveness of syllabification was found to be contingent on the specific words being processed. These findings suggest that while ATA techniques can improve reading accessibility, their varying impacts highlight the need for tailored approaches based on the reader's needs.

Place, publisher, year, edition, pages
2024.
National Category
Natural Language Processing
Identifiers
URN: urn:nbn:se:liu:diva-212604OAI: oai:DiVA.org:liu-212604DiVA, id: diva2:1947117
Conference
The Tenth Swedish Language Technology Conference (SLTC), November 27-29, 2024
Available from: 2025-03-25 Created: 2025-03-25 Last updated: 2025-04-02Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Paper

Authority records

Holmer, DanielJönsson, Arne

Search in DiVA

By author/editor
Holmer, DanielJönsson, Arne
By organisation
Human-Centered SystemsFaculty of Science & Engineering
Natural Language Processing

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 52 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf