Details
| Original language | English |
|---|---|
| Title of host publication | Artificial Intelligence in Education |
| Subtitle of host publication | 22nd International Conference, AIED 2021, Utrecht, The Netherlands, June 14–18, 2021, Proceedings, Part II |
| Editors | Ido Roll, Danielle McNamara, Sergey Sosnovsky, Rose Luckin, Vania Dimitrova |
| Place of Publication | Cham |
| Pages | 196-201 |
| Number of pages | 6 |
| ISBN (electronic) | 978-3-030-78270-2 |
| Publication status | Published - 12 Jun 2021 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 12749 LNAI |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
Illustrations are widely used in education, and sometimes, alternatives are not available for visually impaired students. Therefore, those students would benefit greatly from an automatic illustration description system, but only if those descriptions were complete, correct, and easily understandable using a screenreader. In this paper, we report on a study for the assessment of automated image descriptions. We interviewed experts to establish evaluation criteria, which we then used to create an evaluation questionnaire for sighted non-expert raters, and description templates. We used this questionnaire to evaluate the quality of descriptions which could be generated with a template-based automatic image describer. We present evidence that these templates have the potential to generate useful descriptions, and that the questionnaire identifies problems with description templates.
Keywords
- Accessibility, Automatic image description, Blind and visually impaired, Educational resources
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
Cite this
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Artificial Intelligence in Education: 22nd International Conference, AIED 2021, Utrecht, The Netherlands, June 14–18, 2021, Proceedings, Part II. ed. / Ido Roll; Danielle McNamara; Sergey Sosnovsky; Rose Luckin; Vania Dimitrova. Cham, 2021. p. 196-201 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12749 LNAI).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Evaluation of Automated Image Descriptions for Visually Impaired Students
AU - Hoppe, Anett
AU - Morris, David
AU - Ewerth, Ralph
N1 - Funding Information: This work is financially supported by the German Federal Ministry of Education and Research (BMBF) and the European Social Fund (ESF) (Project InclusiveOCW, no. 01PE17004).
PY - 2021/6/12
Y1 - 2021/6/12
N2 - Illustrations are widely used in education, and sometimes, alternatives are not available for visually impaired students. Therefore, those students would benefit greatly from an automatic illustration description system, but only if those descriptions were complete, correct, and easily understandable using a screenreader. In this paper, we report on a study for the assessment of automated image descriptions. We interviewed experts to establish evaluation criteria, which we then used to create an evaluation questionnaire for sighted non-expert raters, and description templates. We used this questionnaire to evaluate the quality of descriptions which could be generated with a template-based automatic image describer. We present evidence that these templates have the potential to generate useful descriptions, and that the questionnaire identifies problems with description templates.
AB - Illustrations are widely used in education, and sometimes, alternatives are not available for visually impaired students. Therefore, those students would benefit greatly from an automatic illustration description system, but only if those descriptions were complete, correct, and easily understandable using a screenreader. In this paper, we report on a study for the assessment of automated image descriptions. We interviewed experts to establish evaluation criteria, which we then used to create an evaluation questionnaire for sighted non-expert raters, and description templates. We used this questionnaire to evaluate the quality of descriptions which could be generated with a template-based automatic image describer. We present evidence that these templates have the potential to generate useful descriptions, and that the questionnaire identifies problems with description templates.
KW - Accessibility
KW - Automatic image description
KW - Blind and visually impaired
KW - Educational resources
UR - http://www.scopus.com/inward/record.url?scp=85126586388&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-78270-2_35
DO - 10.1007/978-3-030-78270-2_35
M3 - Conference contribution
SN - 978-3-030-78269-6
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 196
EP - 201
BT - Artificial Intelligence in Education
A2 - Roll, Ido
A2 - McNamara, Danielle
A2 - Sosnovsky, Sergey
A2 - Luckin, Rose
A2 - Dimitrova, Vania
CY - Cham
ER -