Literature Reviews
Reviewed research papers, articles, and publications relevant to digital accessibility.
8 results found tagged image descriptions.
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"It's Complicated": Negotiating Accessibility and (Mis)Representation in Image Descriptions of Race, Gender, and Disability
This qualitative study investigates how screen reader users who are also Black, Indigenous, People of Color (BIPOC), non-binary, and/or transgender navigate the complex landscape of image descriptions, particularly regarding how appearance characteri…
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Diffscriber: Describing Visual Design Changes to Support Mixed-Ability Collaborative Presentation Authoring
This paper presents Diffscriber, a system that identifies and describes visual design changes made to slide presentations, enabling blind and visually impaired (BVI) presenters to meaningfully participate in collaborative slide authoring with sighted…
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What's in an ALT Tag? Exploring Caption Content Priorities through Collaborative Captioning
This paper investigates what makes a good image caption through a novel collaborative captioning methodology. Six pairs of blind and sighted partners—including married couples, friends, and roommates—worked together to create and refine captions for …
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From Automation to User Empowerment: Investigating the Role of a Semi-automatic Tool in Social Media Accessibility
This paper presents SONAAR (Social Networks Accessible Authoring), a semi-automatic tool designed to improve social media accessibility by combining AI-powered image recognition with user-generated descriptions. The research addresses a persistent pr…
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"That's in the eye of the beholder": Layers of Interpretation in Image Descriptions for Fictional Representations of People with Disabilities
This paper investigates how to create accurate and sensitive image descriptions for fictional representations of people with disabilities — a challenge that arises when real subjects cannot be consulted about their preferred identity terminology. The…
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Authoring accessible media content on social networks
This paper investigates why user-generated visual content on social media remains overwhelmingly inaccessible to blind and visually impaired users, despite platforms offering tools to add alternative descriptions. The researchers conducted a two-phas…
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Surfacing Variations to Calibrate Perceived Reliability of MLLM-generated Image Descriptions
This paper addresses a critical safety problem in AI-powered visual access technology: multimodal large language models (MLLMs) like GPT-4o, Gemini, and Claude produce fluent, confident image descriptions that can contain fabricated content, misinter…
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Context-Aware Image Descriptions for Web Accessibility
This paper addresses a fundamental limitation of current AI-generated image descriptions: they describe images in isolation without considering the surrounding webpage context. When blind and low-vision (BLV) users encounter images on the web, what t…