Case Study

Neurotechnology developed an image-to-text solution for the Lithuanian Audiosensory Library (LAB) to improve the accessibility of visual content in digital publications for people with reading difficulties.

The same workflow turns illustrations, diagrams, maps and artwork into screen-reader-ready descriptions – in Lithuanian, and adaptable to other languages.

The Lithuanian Audiosensory Library (LAB) sought a way to make visual information in digital publications more accessible to its users. While textual content can already be processed by assistive technologies, visual elements often remain inaccessible, limiting access to educational, scientific and cultural materials.

According to LAB, more than 300,000 people in Lithuania are unable to read standard printed text due to various disabilities, while only about 15 percent of newly published books in the country are currently adapted to their needs.

To address this challenge, LAB selected Neurotechnology to develop an AI-based solution capable of automatically converting visual content into descriptive Lithuanian text. The solution is being integrated into ELVIS, the Electronic Publication Management System, operated by LAB, enabling users to access information contained in illustrations, diagrams and other visual elements through screen reader software.

"For people who cannot access visual information in digital publications, creating meaningful image descriptions has traditionally been a time-consuming and resource-intensive process", said a spokesperson from LAB. "Working with Neurotechnology allowed us to quickly move from concept to implementation. Their team developed a solution that helps make visual content more accessible while fitting smoothly into our existing content adaptation workflow." A spokesperson from the Lithuanian Audiosensory Library (LAB)

The solution uses a combination of computer vision, optical character recognition and large language model technologies. Computer vision algorithms identify visual elements within an image, while OCR extracts embedded text. This information is then processed by language models that generate detailed descriptions in the Lithuanian language.

By combining image understanding and natural language generation in a single workflow, the system can automatically transform illustrations and various image types into accessible text suitable for screen reader applications.

The system is designed to process various types of visual material, including:

1. Illustrations – The tool identifies key objects, people, scenes and visual elements, then converts them into a structured text description.
2. Diagrams and schemes – The AI solution can interpret visual structures and describe the main components of diagrams or schematic images.
3. Maps and historical visuals – Complex visual materials, such as historical maps or educational illustrations, can be described in a way that helps users understand the essential information.
4. Artwork and cultural content – Detailed descriptions may include the type of image, dominant colors, emotional tone or artistic style, depending on the content.

"While the underlying technology relies on advanced AI models, the project's primary goal was straightforward: to make visual content more accessible," said Vytas Mulevičius, NLP Team Lead at Neurotechnology. "By transforming images into descriptive text, the solution helps users access information that might otherwise remain unavailable." Vytas Mulevičius, NLP Team Lead at Neurotechnology

As a result, visual information that would previously require manual adaptation can now be automatically transformed into accessible Lithuanian-language descriptions, helping expand access to educational, scientific and cultural content.

Because the solution produces clean, structured text, the same descriptions can also be voiced with text-to-speech to create audio versions of visual content – extending the workflow toward audiobook-style production for users who prefer listening to reading.

The Lithuanian Audiosensory Library project demonstrates how artificial intelligence can be used to improve information accessibility and create more inclusive digital experiences.

The same technology can be adapted for a wide range of applications, including digital publishing, education and e-learning, document processing, archives, cultural heritage projectsaudiobook-style audio-content production and other environments where visual information needs to be made more accessible and searchable.

Although developed for Lithuanian, the same pipeline can generate descriptions in other languages, making it suitable for publishers and educational content providers working across multiple markets.

For public-sector bodies, libraries and publishers, automated image descriptions also help meet growing digital-accessibility requirements such as the European Accessibility Act and WCAG.

Neurotechnology develops custom artificial intelligence solutions based on natural language processing, computer vision and other AI technologies for public and private sector organizations, helping automate complex information processing tasks and improve access to digital content.