arXiv:2606.09846v1 Announce Type: cross Abstract: Visual art remains largely inaccessible to blind and low-vision (BLV) audiences due to brief or absent alt-text, which rarely conveys the sensory, spatial, or emotional qualities of an artwork. This study presents an automated workflow that generates multi-sensory art descriptions and synchronized audio narration using large language models and text-to-speech services. The system, orchestrated through Zapier, converts uploaded images into rich narrative captions without human intervention, enabling rapid, scalable production of accessible media
Advances in large language models and text-to-speech technology, combined with orchestration tools, have reached a point where fully automated, multi-sensory content generation for accessibility is feasible.
This development highlights the increasing capability of AI agents to automate complex creative and analytical tasks, opening up new avenues for accessibility and content generation across various fields.
The barrier to creating rich, descriptive content for visual media, especially for visually impaired audiences, is significantly lowered, enabling scalable production without human intervention.
- · AI software developers
- · Accessibility technology sector
- · Content creators (with AI tools)
- · Blind and low-vision communities
Automated generation of detailed, narrative-driven descriptions for visual content becomes widely available.
The demand for manual alt-text creation decreases, while the overall volume and richness of accessible digital content increases dramatically.
AI-generated multi-sensory experiences become a standard feature across digital platforms, potentially influencing new forms of art and educational content.
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Read at arXiv cs.CL