@inproceedings{aissa-etal-2025-iread4skills,
    title = "The i{R}ead4{S}kills Intelligent Complexity Analyzer",
    author = "Aissa, Wafa  and
      Amaro, Raquel  and
      Antunes, David  and
      Ba{\~n}eras-Roux, Thibault  and
      Baptista, Jorge  and
      Catala, Alejandro  and
      Correia, Lu{\'i}s  and
      Fran{\c{c}}ois, Thomas  and
      Garcia, Marcos  and
      Izquierdo-{\'A}lvarez, Mario  and
      Mamede, Nuno  and
      Martins, Vasco  and
      Neves, Miguel  and
      Ribeiro, Eug{\'e}nio  and
      Rey, Sandra Rodriguez  and
      Vanzeveren, Elodie",
    editor = {Habernal, Ivan  and
      Schulam, Peter  and
      Tiedemann, J{\"o}rg},
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2025.emnlp-demos.6/",
    pages = "73--84",
    ISBN = "979-8-89176-334-0",
    abstract = "We present the iRead4Skills Intelligent Complexity Analyzer, an open-access platform specifically designed to assist educators and content developers in addressing the needs of low-literacy adults by analyzing and diagnosing text complexity. This multilingual system integrates a range of Natural Language Processing (NLP) components to assess input texts along multiple levels of granularity and linguistic dimensions in Portuguese, Spanish, and French. It assigns four tailored difficulty levels using state-of-the-art models, and introduces four diagnostic yardsticks{---}textual structure, lexicon, syntax, and semantics{---}offering users actionable feedback on specific dimensions of textual complexity. Each component of the system is supported by experiments comparing alternative models on manually annotated data."
}