36.1006, Calls: Langues et Parole - "Lisibilité et Complexité Textuelle / Readability and Textual Complexity" (Jrnl)

[The LINGUIST List]

LINGUIST List: Vol-36-1006. Fri Mar 21 2025. ISSN: 1069 - 4875.

Subject: 36.1006, Calls: Langues et Parole - "Lisibilité et Complexité Textuelle / Readability and Textual Complexity" (Jrnl)

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Managing Editor: Justin Fuller
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Editor for this issue: Justin Fuller <justin at linguistlist.org>

================================================================


Date: 21-Mar-2025
From: Marcos Garcia [marcos.garcia.gonzalez at usc.gal]
Subject: Langues et Parole - "Lisibilité et Complexité Textuelle / Readability and Textual Complexity" (Jrnl)


Journal: Langues et Parole
Issue: Lisibilité et Complexité Textuelle / Readability and Textual
Complexity
Call Deadline: 31-May-2025

(English version below)
Langues et Parole
https://revistes.uab.cat/languesparole/
Appel à Contributions – Numéro Spécial: Lisibilité et Complexité
Textuelle
La revue Langues et Parole invite les chercheurs à soumettre leurs
contributions pour un numéro spécial consacré à la lisibilité et la
complexité textuelle. Ce numéro vise à explorer des approches
théoriques et méthodologiques, ainsi que des applications pratiques,
dans un domaine crucial pour l’analyse des compétences en lecture et
la création d'outils pédagogiques.
Thème du numéro spécial
La complexité et la lisibilité des textes sont des axes de recherche
clés dans l’évaluation des compétences en lecture, en particulier dans
des contextes d’apprentissage diversifiés. Ce numéro spécial cherche à
rassembler des travaux qui combinent linguistique, technologies de la
langue et intelligence artificielle (IA) appliquée, pour mieux
comprendre et évaluer la lisibilité et la complexité des textes. En
lien avec le Cadre Européen Commun de Référence pour les Langues
(CECR; Council of Europe, 2020), les soumissions pourront aborder des
études visant à adapter les niveaux de complexité textuelle pour des
lecteurs de niveaux variés (Cunningham & Mesmer, 2014).
Sujets d'intérêt
Les propositions peuvent inclure, sans s’y limiter, les thèmes
suivants :
- Évaluation automatique de la lisibilité: nouvelles méthodes et
modèles d'analyse, allant des mesures linguistiques classiques aux
approches modernes basées sur l'apprentissage profond et les modèles
de grande ampleur (Large Language Models), comme décrit, par exemple,
dans Lee et al. (2021).
- Études sur la complexité lexicale et syntaxique: analyses de la
richesse lexicale, de la structure syntaxique et de la cohésion
textuelle (Dahl, 2007; Collins-Thompson, 2014; Chen & Meurers, 2018),
avec des applications pour des corpus annotés par niveaux de
complexité, utilisés dans des environnements pédagogiques.
- Applications pédagogiques des technologies de TAL: méthodes et
outils Traitement Automatique de Langues (TAL) pour adapter les textes
en fonction des besoins spécifiques des apprenants, en tenant compte
des aspects multilingues et culturels (OECD, 2013; UNESCO, 2020). Les
contributions pourront par exemple explorer des solutions basées sur
des lexiques de complexité (Blanco Escoda et al, 2024) ou des outils
d'évaluation en ligne (Ribeiro et al. 2024).
- Prédiction et évaluation de la complexité textuelle : développement
de techniques d’évaluation en temps réel, avec un accent sur
l’interface utilisateur et l’accessibilité numérique, pour répondre
aux besoins spécifiques des formateurs et des apprenants (Chen &
Meurers, 2016).
Soumission des Articles
Les articles peuvent être rédigés rédigées en une langue romane
(espagnol, en français, en catalan) ou en anglais, pour refléter le
caractère multilingue de l’édition spéciale. Ils seront évalués selon
des critères de rigueur scientifique, de pertinence du sujet et de
leur contribution aux domaines de la lisibilité et de la complexité
textuelle. 
https://revistes.uab.cat/languesparole/about/submissions 
Dates importantes
- Soumission initiale : 31 mai 2025
- Notification aux auteurs : 3 juillet 2025
- Soumission finale : 20 septembre 2025
- Date de parution prévue:  avant the 31 decembre 2025
Pour toute question ou demande d’information, veuillez contacter
l'équipe éditoriale
à https://revistes.uab.cat/languesparole/about/contact .
Références
Blanco Escoda, X., Amaro, R., François, T., & Garcia, M.
(2023). iRead4Skills - Baselines for complexity lexicons definition.
Zenodo. https://doi.org/10.5281/zenodo.10069793   
Chen, X., & Meurers, D. (2016). CTAP: A web-based tool supporting
automatic complexity analysis. Proceedings of CL4LC, 113–119.  
Chen, X., & Meurers, D. (2018). Word frequency and readability:
Predicting the text-level readability with a lexical-level
attribute. Journal of Research in Reading, 41(3), 486–510.  
Collins-Thompson, K. (2014). Computational assessment of text
readability: A survey of current and future research. International
Journal of Applied Linguistics, 165(2), 97–135.  
Council of Europe. (2020). Common European Framework of Reference for
Languages: Learning, teaching, assessment – Companion volume.
Strasbourg: Council of Europe
Publishing. https://www.coe.int/lang-cefr   
Cunningham, J. W., & Mesmer, H. A. (2014). Quantitative measurement of
text difficulty: What’s the use? Elementary School Journal, 115,
255–269.  
Dahl, O. (2007). Definitions of complexity. Proceedings of the
Colloquium on Complexity, Accuracy and Fluency in Second Language Use,
Learning & Teaching, 41–46.  
Douglas, Y., & Miller, S. (2016). Syntactic and lexical complexity of
reading correlates with complexity of writing in adults. International
Journal of Business Administration, 7(4).
Imperial, J. M. (2021). Knowledge-rich BERT embeddings for readability
assessment. arXiv preprint arXiv:2106.07935   
Lee, B. W., Jang, Y. S., & Lee, J. (2021). Pushing on text readability
assessment: A transformer meets handcrafted linguistic
features. Proceedings of EMNLP 2021, 10, 669–10,686.  
OECD. (2013). Technical report of the survey of adult skills (PIAAC).
OECD Publishing.  
Ribeiro, E., Mamede, N., & Baptista, J. (2024). Automatic text
readability assessment in European Portuguese.Proceedings of PROPOR
2024, 97–107.  
UNESCO. (2020). Literacy. UNESCO Institute for
Statistics. https://uis.unesco.org/node/3079547   
Wilkens, R., Alfter, D., Wang, X., Pintard, A., Tack, A., Yancey, K.
P., & François, T. (2022). FABRA: French aggregator-based readability
assessment toolkit. Proceedings of ELRA, 1217–1233.
------
Langues et Parole
https://revistes.uab.cat/languesparole/
Call for Papers – Special Issue: Readability and Textual Complexity
The journal Langues et Parole invites researchers to submit
contributions for its special issue dedicated to readability and
textual complexity. This issue aims to explore theoretical and
methodological approaches, as well as practical applications, in a
crucial area for analyzing reading skills and developing educational
tools.
Theme of the Special Issue
The complexity and readability of texts are key research areas in
assessing reading skills, particularly in diverse learning contexts.
This special issue seeks to gather studies that combine linguistics,
language technologies, and applied artificial intelligence (AI) to
better understand and evaluate readability and textual complexity. In
connection with the Common European Framework of Reference for
Languages (CEFR; Council of Europe, 2020), submissions may include
studies that aim to adapt textual complexity levels for readers with
different proficiency levels (Cunningham & Mesmer, 2014).
Topics of Interest
Proposals may include, but are not limited to, the following topics:
- Automatic readability assessment: New methods and analysis models,
ranging from traditional linguistic measures to modern approaches
based on deep learning and large language models, as described, for
example, in Lee et al. (2021).
- Studies on lexical and syntactic complexity: Analyses of lexical
richness, syntactic structure, and textual cohesion (Dahl, 2007;
Collins-Thompson, 2014; Chen & Meurers, 2018), with applications for
corpora annotated by complexity levels used in educational
environments.
- Educational applications of NLP technologies: Methods and tools for
Natural Language Processing (NLP) to adapt texts to learners’ specific
needs, taking into account multilingual and cultural aspects (OECD,
2013; UNESCO, 2020). Contributions may explore solutions based on
complexity lexicons (Blanco Escoda et al., 2024) or online assessment
tools (Ribeiro et al., 2024).
- Prediction and evaluation of textual complexity: Development of
real-time evaluation techniques, with a focus on user interface and
digital accessibility, to meet the specific needs of educators and
learners (Chen & Meurers, 2016).
Paper submission
Papers may be written in a Romance language (Spanish, French, or
Catalan) or in English, to reflect the multilingual nature of this
special edition. Submissions will be evaluated based on scientific
rigor, topic relevance, and their contribution to the fields of
readability and textual complexity.
https://revistes.uab.cat/languesparole/about/submissions
Important Dates
    • Initial submission deadline: May 31, 2025
    • Notification to authors: July 3, 2025
    • Final submission deadline: September 20, 2025
    • Expected publication date: Before December 31, 2025
For any questions or further information, please contact the editorial
team at https://revistes.uab.cat/languesparole/about/contact.
References
Blanco Escoda, X., Amaro, R., François, T., & Garcia, M.
(2023). iRead4Skills - Baselines for complexity lexicons definition.
Zenodo. https://doi.org/10.5281/zenodo.10069793   
Chen, X., & Meurers, D. (2016). CTAP: A web-based tool supporting
automatic complexity analysis. Proceedings of CL4LC, 113–119.  
Chen, X., & Meurers, D. (2018). Word frequency and readability:
Predicting the text-level readability with a lexical-level
attribute. Journal of Research in Reading, 41(3), 486–510.  
Collins-Thompson, K. (2014). Computational assessment of text
readability: A survey of current and future research. International
Journal of Applied Linguistics, 165(2), 97–135.  
Council of Europe. (2020). Common European Framework of Reference for
Languages: Learning, teaching, assessment – Companion volume.
Strasbourg: Council of Europe
Publishing. https://www.coe.int/lang-cefr   
Cunningham, J. W., & Mesmer, H. A. (2014). Quantitative measurement of
text difficulty: What’s the use? Elementary School Journal, 115,
255–269.  
Dahl, O. (2007). Definitions of complexity. Proceedings of the
Colloquium on Complexity, Accuracy and Fluency in Second Language Use,
Learning & Teaching, 41–46.  
Douglas, Y., & Miller, S. (2016). Syntactic and lexical complexity of
reading correlates with complexity of writing in adults. International
Journal of Business Administration, 7(4).
Imperial, J. M. (2021). Knowledge-rich BERT embeddings for readability
assessment. arXiv preprint arXiv:2106.07935   
Lee, B. W., Jang, Y. S., & Lee, J. (2021). Pushing on text readability
assessment: A transformer meets handcrafted linguistic
features. Proceedings of EMNLP 2021, 10, 669–10,686.  
OECD. (2013). Technical report of the survey of adult skills (PIAAC).
OECD Publishing.  
Ribeiro, E., Mamede, N., & Baptista, J. (2024). Automatic text
readability assessment in European Portuguese.Proceedings of PROPOR
2024, 97–107.  
UNESCO. (2020). Literacy. UNESCO Institute for
Statistics. https://uis.unesco.org/node/3079547   
Wilkens, R., Alfter, D., Wang, X., Pintard, A., Tack, A., Yancey, K.
P., & François, T. (2022). FABRA: French aggregator-based readability
assessment toolkit. Proceedings of ELRA, 1217–1233.

Linguistic Field(s): Applied Linguistics
                     Computational Linguistics
                     Text/Corpus Linguistics
                     Writing Systems

Subject Language(s): Catalan (cat)
                     English (eng)
                     French (fra)
                     Spanish (spa)

Language Family(ies): Romance



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