# Evaluation of Automated Image Descriptions for Visually Impaired Students

arXiv: https://arxiv.org/abs/2106.15553 · HTML: https://mlsanity.com/paper/2106.15553/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 11 references that are in the map.
- First posted on arXiv 29 Jun 2021.

## Builds on (most cited first, 5 of 5)

- [A Diagram Is Worth A Dozen Images](https://mlsanity.com/paper/1603.07396/) (2016)
- [Engaging Image Captioning Via Personality](https://mlsanity.com/paper/1810.10665/) (2018)
- [Multi-Scale Attention with Dense Encoder for Handwritten Mathematical Expression Recognition](https://mlsanity.com/paper/1801.03530/) (2018)
- [Attend to You: Personalized Image Captioning with Context Sequence Memory Networks](https://mlsanity.com/paper/1704.06485/) (2017)
- [Pattern Generation Strategies for Improving Recognition of Handwritten Mathematical Expressions](https://mlsanity.com/paper/1901.06763/) (2019)

## Built on by (most cited first, 1 of 1)

- [A Systematic Survey on Image Description Techniques for STEM Domains](https://mlsanity.com/paper/2607.21611/) (2026)

## Abstract (arXiv)

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.