Alt4Blind: A User Interface to Simplify Charts Alt-Text Creation

Omar Moured, Shahid Ali Farooqui, Karin Muller, Sharifeh Fadaeijouybari, Thorsten Schwarz +2 more
5/29/2024
cs.CVcs.HC

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Abstract

Alternative Texts (Alt-Text) for chart images are essential for making graphics accessible to people with blindness and visual impairments. Traditionally, Alt-Text is manually written by authors but often encounters issues such as oversimplification or complication. Recent trends have seen the use of AI for Alt-Text generation. However, existing models are susceptible to producing inaccurate or misleading information. We address this challenge by retrieving high-quality alt-texts from similar chart images, serving as a reference for the user when creating alt-texts. Our three contributions are as follows: (1) we introduce a new benchmark comprising 5,000 real images with semantically labeled high-quality Alt-Texts, collected from Human Computer Interaction venues. (2) We developed a deep learning-based model to rank and retrieve similar chart images that share the same visual and textual semantics. (3) We designed a user interface (UI) to facilitate the alt-text creation process. Our preliminary interviews and investigations highlight the usability of our UI. For the dataset and further details, please refer to our project page: https://moured.github.io/alt4blind/.

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Cite this paper

@article{moured2024altblind,
  title  = {Alt4Blind: A User Interface to Simplify Charts Alt-Text Creation},
  author = {Omar Moured and Shahid Ali Farooqui and Karin Muller and Sharifeh Fadaeijouybari and Thorsten Schwarz and Mohammed Javed and Rainer Stiefelhagen},
  year   = {2024},
  eprint = {2405.19111},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2405.19111v1}
}

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