Abstract
We are currently developing a system that facilitates teachers of translation to evaluate and select suitable document segments as materials for translator training. The system needs to satisfy several requirements. Firstly, because translation is an act that deals with documents and not with texts in linguistics, it takes into account documentational features. Secondly, it should facilitate teachers to select suitable documentational segments that usually consist of several paragraphs, as translation generally requires a long time, especially for trainees. Thirdly, it should facilitate teachers to compare different segments in the same document or from different documents, because teachers often need to use more than one material in a class or use progressively advanced materials in a course. The system should preferably relate documentational features to translation competences. These requirements make the system different from most existing text analysis systems. In the demo, we show the trial version of the system, explaining the core functionalities together with the background design concepts.
Supported by JSPS KAKENHI Grant-in-Aid (S) Grant Number 19H05660.
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References
Automatic Readability Checker Homepage. https://readabilityformulas.com/free-readability-formula-tests.php. Accessed 7 July 2023
Baayen, R.H.: Word Frequency Distributions. Kluwer, Dordrecht (2001)
Chodkiewicz, M.: The EMT framework of reference for competences applied to translation: perceptions by professional and student translators. J. Specialised Transl. 17, 37–54 (2012)
CVLA: CEFR-based Vocabulary Level Analyzer (ver. 2.0) Homepage. https://cvla.langedu.jp/. Accessed 7 July 2023
Dubay, W.H.: The Principles of Readability. Impact Information, Costa Mesa (2004)
Esfandiari, M.R., Shokrpour, N., Rahimi, F.: An evaluation of the EMT: compatibility with the professional translator’s needs. Cogent Arts Hum. 6(1), 1–17 (2019)
European Master’s in Translation: Competence framework 2022. https://commission.europa.eu/system/files/2022-11/emt_competence_fwk_2022_en.pdf. Accessed 8 July 2023
EnglishProfile: The CEFR for English. https://www.englishprofile.org/wordlists/. Accessed 14 July 2023
Flesch, R.F.: A new readability yardstick. J. Appl. Psychol. 32(3), 221–233 (1948)
Kageura, K.: The status of documents and related concepts in translation and in library science. In: A-LIEP 2019, pp. 1–13 (2019)
Kageura, K.: What do translators translate? AAMT J. 71, 14–19 (2019). (in Japanese)
Kageura, K., Yamamoto, M., Miyata, R.: A typology of basic translation competences: towards diagnosing and assessing acts in core translation processes in terms of competences. In: The 23rd ITRI International Conference (2023)
Kincaid, J.P., Fishburne, R.P., Jr., Rogers, R.L., Chissom, B.S.: Derivation of new readability formulas (Automated Readability Index, Fog Count and Flesch Reading Ease Formula) for Navy enlisted personnel. University of Central Florida, Millington, Institute for Simulation and Training (1975)
Lewrenz, A.S.: A vocabulary grade placement formula. J. Exp. Educ. 3(3), 236 (1935)
Lexos Homepage. http://lexos.wheatoncollege.edu/statistics. Accessed 7 July 2023
Miyata, R., Miyauchi, T.: Metalanguages for source document analysis: properties and elements. In: Miyata, R., Yamada, M., Kageura, K. (eds.) Metalanguages for Dissecting Translation Processes: Theoretical Development and Practical Applications, pp. 63–79. Routledge, London (2022)
Nagel, S.: News Dataset Available site (2016). https://commoncrawl.org/2016/10/news-dataset-available/. Accessed 14 July 2023
Piao, H., Kageura, K.: A review for the design of a translation education curriculum aiming at the development of translator competence: Towards transferring “knowing how” through “knowing that”. Studies in Lifelong Learning Infrastructure Management, vol. 47, pp. 1–17 (2022). (in Japanese)
readability 0.3.1. https://pypi.org/project/readability/. Accessed 14 July 2023
TextInspector Homepage. https://textinspector.com/. Accessed 7 July 2023
Text Analytics with Sketch Engine Homepage. https://www.sketchengine.eu/tools-for-text-analysis/. Accessed 7 July 2023
Tuldava, J.: Methods of Quantitative Linguistics. Wissenschaftlicher Verlag Trier, Trier (1995)
Uchida, S., Negishi, M.: Assigning CEFR-J levels to English texts based on textual features. In: Proceedings of the 4th Asia Pacific Corpus Linguistics Conference, pp. 463–467 (2018)
Acknowledgements
This work is partially supported by JSPS KAKENHI Grant-in-Aid (S) Grant Number 19H05660. The authors would like to thank Dr. Atsushi Fujita of National Institute of Information and Communications Technology for constructive discussion.
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Abekawa, T., Miyata, R., Kageura, K. (2023). QRDP: A System that Facilitates the Selection of English Materials for Translator Education. In: Goh, D.H., Chen, SJ., Tuarob, S. (eds) Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration. ICADL 2023. Lecture Notes in Computer Science, vol 14457. Springer, Singapore. https://doi.org/10.1007/978-981-99-8085-7_19
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