Easy-to-Read (E2R) is an approach to content creation that emphasizes simplicity and clarity in language to make texts more accessible to readers with cognitive challenges or learning disabilities. The Spanish version of E2R is called Lectura Fácil (LF). E2R and its variants, such as LF, focus on straightforward language and structure to enhance readability. The manual production of such texts is both time and resource expensive. In this work, we have developed LFWriteAssist, an authoring support tool that aligns with the guidelines of LF. It is underpinned by the functionalities of LanguageTool, a free and open source grammar, style and spelling checker. Our tool assists in ensuring compliance with LF standard, provides definitions for complex, polysemic, or infrequently used terms, and acronym extensions. The tool is primarily targeted at LF creators, as it serves as an authoring aid, identifying any rule infringements and assisting with language simplifications. However, it can be used by anyone who seek to enhance text readability and inclusivity. The tool’s code is made available as open source, thereby contributing to the wider effort of creating inclusive and comprehensible content.

The process of adapting and creating Easy-to-Read (E2R) texts is very expensive and time-consuming. Due to the success of Large Language Models (LLMs) such as ChatGPT and their ability to generate written language, it is likely to think that such models can help in the adaptation or creation of text in E2R. In this paper, we explore the concept of E2R, its underlying principles and applications, and provides a preliminary study on the usefulness of ChatGPT-4 for E2R text adaptation. We focus on the Spanish language and its E2R variant, Lectura Fácil (LF). We consider a range of prompts that can be used and the differences in output that this produces. We then carry out a three-folded evaluation on 10 texts adapted by ChatGPT-4: (1) an automated evaluation to check values related to the readability of texts, (2) a checklist-based manual evaluation (for which we also propose three new capabilities) and (3) a users’ evaluation with people with cognitive disabilities. We show that it is difficult to choose the best prompt to make ChatGPT-4 adapt texts to LF. Furthermore, the generated output does not follow the E2R text rules, so it is often not suitable for the target audience.