Our latest whitepaper presents an innovative approach to improving web accessibility for visually impaired individuals by automating the generation of alternative text (alt text) using large language models (LLMs). Alt text provides a brief description of an image, which is essential for helping screen reader users understand visual content and enhancing their overall web experience.

The paper addresses the significant challenges content creators face in manually generating accurate and descriptive alt text for the increasing volume of visual content on the web. Manual creation is not only time-consuming and resource-intensive but also prone to inconsistencies in quality, which can impact user experience and pose legal and compliance risks. Automating this process can save time and costs, ensure consistent quality, and enhance search engine optimization (SEO).

Leveraging the capabilities of advanced LLMs, specifically the Gemini model, the proposed solution processes images individually and generates detailed prompts derived from surrounding HTML content to produce descriptive alt text. This approach aims to overcome the limitations of existing methods, such as rule-based systems and traditional machine learning techniques, which often struggle to capture the nuances of complex image content and generate contextually relevant descriptions.

The evaluation of the Gemini model's performance, using both quantitative metrics like the BLEU score and qualitative assessments by human experts, demonstrates its potential in producing accurate and informative alt text. However, the paper acknowledges the need for further improvements to address challenges such as handling complex images and ensuring consistency across different image domains.

By automating alt text generation, businesses can significantly enhance the accessibility of their websites for visually impaired users, improve overall user experience, and ensure legal compliance. The whitepaper concludes by emphasizing the promise of large language models in creating a more inclusive digital landscape and the need for ongoing research to refine the approach.

Read our whitepaper now!