Have a personal or library account? Click to login

Using a parallel corpus to adapt the Flesch Reading Ease formula to Czech

Open Access
|Dec 2021

References

  1. [1] Flesch, R. (1948). A New Readability Yardstick. Journal of Applied Psychology, 32, pages 221–233.10.1037/h0057532
  2. [2] Rosen, A. (2016). InterCorp – a look behind the façade of a parallel corpus. In Polskojęzyczne Korpusy Równoległe Polish-Language Parallel Corpora, pages 21–40, Instytut Lingwistyki Stosowanej, Warszawa.
  3. [3] DuBay, W. (2007). Smart Language. Readers, Readability, and the Grading of Text. Impact Information, Costa Mesa, California.
  4. [4] Šlerka, J., and Smolík, F. (2010). Automatická měřítka čitelnosti pro česky psané texty. Studie z Aplikované Lingvistiky, 1, pages 33–44.
  5. [5] Novák, M., Mírovský, J., Rysová, K., Rysová, M., and Hajičová, E. (2019). EVALD 4.0 – Evaluator of Discourse. Accesible at: http://hdl.handle.net/11234/1-3065.
  6. [6] Kincaid, J. P., Fishburne, R. P., Rogers, R. L., Chissom, B. S., and BRANCH, N.T.T.C.M.T.R. (1975). Derivation of New Readability Formulas (Automated Readability Index, Fog Count and Flesch Reading Ease Formula). for Navy Enlisted Personnel. Defense Technical Information Center. Accessible at: https://books.google.cz/books?id=7Z7ENwAACAAJ.
  7. [7] Coleman, M., and Liau, T. L. (1975). A computer readability formula designed for machine scoring. Journal of Applied Psychology, 60, pages 283–284.10.1037/h0076540
  8. [8] McLaughlin, G. H. (1969). SMOG grading – a new readability formula. Journal of Reading, 22, pages 639–646.
  9. [9] Council of Europe. (2018). Common European Framework of Reference for Languages: Learning, Teaching, Asessment. Companion volume. Council of Europe Publishing, Strasbourg. Accesible at: https://www.coe.int/lang-cefr.
  10. [10] Rysová, K., Rysová, M., Mírovský, J., and Novák, M. (2017). Introducing EVALD – Software Applications for Automatic Evaluation of Discourse in Czech. RANLP Proceedings, Bulgaria, pages 634–641.10.26615/978-954-452-049-6_082
  11. [11] Cvrček, V., Čech, R., and Kubát, M. (2020). QuitaUp. Czech National Corpus and University of Ostrava. Accesible at: https://www.korpus.cz/quitaup/.
  12. [12] Dębowski, Ł., Broda, B., Nitoń, B., and Charzyńska, E. (2015). Jasnopis – A Program to Compute Readability of Texts in Polish Based on Psycholinguistic Research. Natural Language Processing and Cognitive Science, 2015 Libreria Editrice Cafoscarina, Venezia, Italy, pages 51–61.
  13. [13] Chen, x., and Meurers, D. (2016). CTAP: A Web-Based Tool Supporting Automatic Complexity Analysis. Apollo – University of Cambridge Repository. Accesible at: https://www.repository.cam.ac.uk/handle/1810/292470.
  14. [14] Flesch, R. (1974). The art of readable writing. 2nd ed. Harper, New York.
  15. [15] DuBay, W. H. (2008). Unlocking Language: Classic Readability Studies. IEEE Transactions on Professional Communication, 51.10.1109/TPC.2008.2007872
  16. [16] Guryanov, I., Yarmakeev, I., Kiselnikov, A., and Harkova, I. (2017). Text Complexity: Periods of Study in Russian Linguistics. Revista Publicando, 4, pages 616–625.
  17. [17] Oborneva, I. V. (2006). Mathematical model for evaluation of didactic texts. Proc of Moscow State Pedag Univ, 4, pages 141–147.
  18. [18] Garais, E.-G. (2011). Web Applications Readability. Romanian Economic Business Review, 5, pages 117–121.
  19. [19] Amstad, T. (1978). Wie verständlich sind unsere Zeitungen? Studenten-Schreib-Service.
  20. [20] Sinha, M., Sharma, S., Dasgupta, T., and Anupam, B. (2012). New Readability Measures for Bangla and Hindi Texts.
  21. [21] Kandel, L., and Moles, A. (1958). Application de l’indice de flesch à la langue française. Cahiers Etudes de Radio-Télévision, 19, pages 253–274.
  22. [22] De Landsheere, G. (1963). Pour une application des tests de lisibilité de Flesch à la langue française. Le Travail Humain, pages 141–154.
  23. [23] Henry, G. (1975). Comment mesurer la lisibilité. Labor, Brussels, Belgium.
  24. [24] François, T., and Fairon, C. (2012). An AI readability formula for French as a foreign language, 477 p.
  25. [25] Solnyshkina, M., Ivanov, V., and Solovyev, V. (2018). Readability Formula for Russian Texts: A Modified Version: 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, Proceedings, Part II, pages 132–145.10.1007/978-3-030-04497-8_11
  26. [26] Čermák, F., and Rosen, A. (2012). The Case of InterCorp, a multilingual parallel corpus. International Journal of Corpus Linguistics, 13, pages 411–427.10.1075/ijcl.17.3.05cer
  27. [27] Straka, M. (2018). UDPipe 2.0 Prototype at CoNLL 2018 UD Shared Task. Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, Association for Computational Linguistics, Brussels, Belgium, pages 197–207.
  28. [28] SciPy 1.0 Contributors, Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T. et al. (2020). SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17, pages 261–272.
  29. [29] https://github.com/vanickovak/ReadabilityFormula.
DOI: https://doi.org/10.2478/jazcas-2021-0044 | Journal eISSN: 1338-4287 | Journal ISSN: 0021-5597
Language: English
Page range: 477 - 487
Published on: Dec 30, 2021
Published by: Slovak Academy of Sciences, Mathematical Institute
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2021 Klára Bendová, published by Slovak Academy of Sciences, Mathematical Institute
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.