Effective communication is essential in society, yet many texts are too complex for a significant portion of the population to understand. This issue has led to the development of movements such as Plain Language (PL) and Easy-to-Read (E2R), both of which aim to make information accessible to everyone.

Plain Language seeks to transform complex documents, such as administrative texts, into clear and comprehensible versions that can be easily understood by the general public. This approach ensures precision while adopting simple language and a well-structured design.

Easy-to-Read, on the other hand, focuses on improving reading and comprehension for individuals with cognitive disabilities, such as dyslexia, attention deficit disorder, autism, or aphasia. The UNE guidelines provide principles for adapting texts into simpler versions in Spanish, ensuring that all individuals can access information, make informed decisions, and fully participate in society.

Currently, adapting texts to Plain Language or Easy-to-Read is a manual process that is time-consuming and resource-intensive. Given the vast amount of information produced daily, this manual approach is no longer sustainable. Artificial Intelligence (AI) and Natural Language Processing (NLP) offer promising solutions for automating this adaptation process.

While most NLP efforts have focused on automatic text simplification, primarily addressing lexical and syntactic complexity, the adaptation of texts to Easy-to-Read and Plain Language demands more advanced strategies to ensure accessibility.

Our research aims to investigate and develop automatic techniques to adapt Spanish texts to these accessible formats. This contribution aspires to promote a more inclusive society where the right to comprehend information is guaranteed for all individuals.