Evaluating the quality of accessible image captions with human raters is difficult, as it may
be difficult for a visually impaired user to know how comprehensive a caption is, whereas a …

The access of visually impaired users to imagery in social media is constrained by the
availability of suitable alt text. It is unknown how imperfections in emerging tools for …

We study how real-time crowdsourcing can be used both for evaluating the value provided
by existing automated approaches and for enabling workflows that provide scalable and …

Blind users rely on alternative text (alt-text) to understand an image; however, alt-text is often
missing. AI-generated captions are a more scalable alternative, but they often miss crucial …

While an important problem in the vision community is to design algorithms that can
automatically caption images, few publicly-available datasets for algorithm development …

One of the ways blind people understand their surroundings is by clicking images and
relying on descriptions generated by image captioning systems. Current work on captioning …

Accessing images online is often difficult for users with vision impairments. This population
relies on text descriptions of images that vary based on website authors' accessibility …

AI image captioning challenges encourage broad participation in designing algorithms that
automatically create captions for a variety of images and users. To create large datasets …

As Automatic Speech Recognition (ASR) improves in accuracy, it may become useful for
transcribing spoken text in real-time for Deaf and Hard-of-Hearing (DHH) individuals. To …

Image captioning is an important task for benchmarking visual reasoning and for enabling
accessibility for people with vision impairments. However, as in many machine learning …