@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://aclanthology.org/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."
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<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.</abstract>
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%0 Conference Proceedings
%T The iRead4Skills Intelligent Complexity Analyzer
%A Aissa, Wafa
%A Amaro, Raquel
%A Antunes, David
%A Bañeras-Roux, Thibault
%A Baptista, Jorge
%A Catala, Alejandro
%A Correia, Luís
%A François, Thomas
%A Garcia, Marcos
%A Izquierdo-Álvarez, Mario
%A Mamede, Nuno
%A Martins, Vasco
%A Neves, Miguel
%A Ribeiro, Eugénio
%A Rey, Sandra Rodriguez
%A Vanzeveren, Elodie
%Y Habernal, Ivan
%Y Schulam, Peter
%Y Tiedemann, Jörg
%S Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-334-0
%F aissa-etal-2025-iread4skills
%X 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.
%U https://aclanthology.org/2025.emnlp-demos.6/
%P 73-84
Markdown (Informal)
[The iRead4Skills Intelligent Complexity Analyzer](https://aclanthology.org/2025.emnlp-demos.6/) (Aissa et al., EMNLP 2025)
ACL
- Wafa Aissa, Raquel Amaro, David Antunes, Thibault Bañeras-Roux, Jorge Baptista, Alejandro Catala, Luís Correia, Thomas François, Marcos Garcia, Mario Izquierdo-Álvarez, Nuno Mamede, Vasco Martins, Miguel Neves, Eugénio Ribeiro, Sandra Rodriguez Rey, and Elodie Vanzeveren. 2025. The iRead4Skills Intelligent Complexity Analyzer. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 73–84, Suzhou, China. Association for Computational Linguistics.