Open Access
SHS Web Conf.
Volume 78, 2020
7e Congrès Mondial de Linguistique Française
Article Number 14006
Number of page(s) 14
Section Syntaxe
Published online 04 September 2020
  1. Alva-Manchego, Bingel, J., Paetzold, G., Scarton, C. et Specia, C. (2017) Learning How to Simplify From Explicit Labeling of Complex-Simplified Text Pairs, Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 295305. [Google Scholar]
  2. Billami, M. B., François, T. et Gala, N. (2018) ReSyf: A French Lexicon with Ranked Synonyms. Proceedings of the 27th International Conference on Computational Linguistics (COLING-2018), Santa Fe, New Mexico, USA, 2570–2581 [Google Scholar]
  3. Brouwers, L., Bernhard, D., Ligozat, A.L. et François, T. (2014) Syntactic Sentence Simplification for French. Proceedings of the 3rd Workshop on Predicting and Improving Text Readability for Target Reader Populations (PITR) at EACL 2014, Gothenburg, Suède, 47–56. [CrossRef] [Google Scholar]
  4. Brunato D., Dell’Orletta F., Venturi G. et Montemagni S. (2014) Defining an annotation scheme with a view to automatic text simplification. Proceedings of the First Italian Conference on Computational Linguistics (CLiC-it 2014), ISBN 978-8-86741-472-7, Pisa, Basili R., Lenci A., and Magnini B. (eds.), published by Pisa University Press srl, Pisa (Italia), 87–92. [Google Scholar]
  5. Cardon, R. (2018) Approche lexicale de la simplification automatique de textes médicaux. Dans Actes de la conférence Traitement Automatique de la Langue Naturelle, TALN 2018, 175–189. [Google Scholar]
  6. Dekker, R.H. et Middell, G. (2011). Computer-supported collation with CollateX: Managing textual variance in an environment with varying requirements. Supporting Digital Humanities, 17–18. [Google Scholar]
  7. Fenoglio I. et Ganascia J-G. (2007) MEDITE: un logiciel pour l’approche comparative de documents de genèse. Revue Genesis, pp. 166–168. [Google Scholar]
  8. Gala, N., Tack, A., Javourey-Drevet, L., François, T. et Ziegler, J.-C. (2020) Alector: A Parallel Corpus of Simplified French Texts with Alignments of Misreadings by Poor and Dyslexic Readers. Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020), poster session. Marseille, France. [Google Scholar]
  9. Gala, N., François, T., Javourey-Drevet, L. et Ziegler, J.-C. (2018) Vers une simplification automatique de textes pour une meilleure compréhension. Dans Langue Française « L’apprentissage de la lecture en français langue maternelle et seconde », Armand Colin, 123131. [Google Scholar]
  10. Gala, N. et Ziegler, J.-C. (2016) Reducing lexical complexity as a tool to increase text accessibility for children with dyslexia. Proceedings of the workshop Computational Linguistics for Linguistic Complexity (CL4LC) at the 26th International Conference on Computational Linguistics (COLING-2016). Osaka, Japon. [Google Scholar]
  11. Koptient, A., Cardon, R. et Grabar, N. (2019) Simplification-induced transformations: typology and some characteristics. In Proceedings of the 18th BioNLP Workshop and Shared Task, Association for Computational Linguistics, Florence, Italy, 309–318. [Google Scholar]
  12. Namer, F. (2000). FLEMM: un analyseur flexionnel du français à base de règles. Traitement Automatique des Langues, 41(2), 523–547. [Google Scholar]
  13. Qi, P., Dozat, T., Zhang, Y. et Manning, C. D. (2018). Universal dependency parsing from scratch. In Proceedings of the CoNLL 2018 shared task: multilingual parsing from raw text to universal dependencies. Brussels, Belgium: Association for Computational Linguistics, 160–170. [Google Scholar]
  14. Rello, L. (2014). DysWebxia: a text accessibility model for people with dyslexia. Ph.D. thesis, Universitat Pompeu Fabra, Barcelona. [Google Scholar]
  15. Saggion, H. (2017) Automatic Text Simplification (Synthesis Lectures on Human Language Technologies). 1 ed. Morgan & Claypool Publishers. [Google Scholar]
  16. Saggion, H., Gomez-Martin, E., Anula, A., Bourg, L. et Etayo, E. (2011) Text simplification in SImplext: Making texts more accessible. Procesamiento del Lenguaje Natural (SEPLN) n° 47, 341–342. [Google Scholar]
  17. Wilkens, R. et Todirascu, A. (2020) Simplifying Coreference Chains for Dyslexic Children. Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020), poster session. Marseille, France. [Google Scholar]
  18. Zorzi, M., Barbiero, C., Facoetti, A., Lonciari, I., Carrozzi, M., Montico, M. et Ziegler, J. C. (2012). Extra-large letter spacing improves reading in dyslexia. Proceedings of the National Academy of Sciences, 109(28), ^ 145:5–11–4:59. [CrossRef] [Google Scholar]
  19. Ziegler, J.-C., Perry, C. et Zorzi, M. (2014). Modeling reading development through phonological decoding and self-teaching: Implications for dyslexia. Philosophical Transactions of the Royal Society B [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.