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Source or target first? Comparison of two post-editing strategies with translation students
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In: https://hal.archives-ouvertes.fr/hal-03546151 ; 2022 (2022)
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Are Easy Language Best Practices Applied in Educational Texts for Children in French?
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In: International Easy Language Day Conference (IELD) 2021 (2021) (2021)
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A Reception Study of Machine-Translated Easy Language Text by Individuals with Reading Difficulties
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In: 3rd International Conference on Translation, Interpreting and Cognition (ICTIC3) (2021) (2021)
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Google Assistant's Interpreter Mode: is it really an interpreter?
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Evaluating the comprehension of Arasaac and Sclera pictographs for the BabelDr patient response interface
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In: Proceedings of the 3rd Swiss conference on barrier-free communication (BfC 2020) pp. 55-63 (2021)
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Linguistic and Ethical Considerations in Easy Language Machine Translation
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In: International Easy Language Day Conference (IELD) 2021 (2021) (2021)
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Experiments for the adaptation of Text2Picto to French
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In: 31st Meeting of Computational Linguistics in The Netherlands (CLIN 31) (2021) (2021)
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A speech translation system for medical dialogue in sign language — Questionnaire on user perspective of videos and the use of Avatar Technology
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In: Proceedings of the 3rd Swiss Conference on Barrier-free Communication (BfC 2020) pp. 46-54 (2021)
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La post-édition monolingue des textes de spécialité dans le domaine de la musique
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Vers une communication médicale adaptée aux personnes sourdes.Le projet BabelDr et les personnages virtuels en langue des signes française de Suisse romande
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In: TLH-Santé2021 (2021) (2021)
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A speech-enabled fixed-phrase translator for healthcare accessibility
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In: Proceedings of the 1st Workshop on NLP for Positive Impact (2021)
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Getting across in medical communication: A corpus-based approach to analyze and improve the comprehensibility of machine translation
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In: Proceedings of the 3rd Swiss conference on barrier-free communication (BfC 2020) pp. 39-45 (2021)
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| 14 |
Predicting the Linguistic Accessibility of Chinese Health Translations: Machine Learning Algorithm Development
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In: ISSN: 2291-9694 ; JMIR medical informatics, Vol. 9, No 10 (2021) P. e30588 (2021)
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| 15 |
Predicting the Linguistic Accessibility of Chinese Health Translations: Machine Learning Algorithm Development
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In: JMIR Med Inform (2021)
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Abstract:
BACKGROUND: Linguistic accessibility has an important impact on the reception and utilization of translated health resources among multicultural and multilingual populations. Linguistic understandability of health translation has been understudied. OBJECTIVE: Our study aimed to develop novel machine learning models for the study of the linguistic accessibility of health translations comparing Chinese translations of the World Health Organization health materials with original Chinese health resources developed by the Chinese health authorities. METHODS: Using natural language processing tools for the assessment of the readability of Chinese materials, we explored and compared the readability of Chinese health translations from the World Health Organization with original Chinese materials from the China Center for Disease Control and Prevention. RESULTS: A pairwise adjusted t test showed that the following 3 new machine learning models achieved statistically significant improvement over the baseline logistic regression in terms of area under the curve: C5.0 decision tree (95% CI –0.249 to –0.152; P<0.001), random forest (95% CI 0.139-0.239; P<0.001) and extreme gradient boosting tree (95% CI 0.099-0.193; P<0.001). There was, however, no significant difference between C5.0 decision tree and random forest (P=0.513). The extreme gradient boosting tree was the best model, achieving statistically significant improvement over the C5.0 model (P=0.003) and the random forest model (P=0.006) at an adjusted Bonferroni P value at 0.008. CONCLUSIONS: The development of machine learning algorithms significantly improved the accuracy and reliability of current approaches to the evaluation of the linguistic accessibility of Chinese health information, especially Chinese health translations in relation to original health resources. Although the new algorithms developed were based on Chinese health resources, they can be adapted for other languages to advance current research in accessible health translation, communication, and promotion.
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Original Paper
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URL: http://www.ncbi.nlm.nih.gov/pubmed/34617914
https://doi.org/10.2196/30588
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8532010/
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Language service provision in the 21st century: challenges, opportunities and educational perspectives for translation studies
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In: ISBN: 9788869234934 ; Bologna Process beyond 2020: Fundamental values of the EHEA pp. 297-303 (2020)
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Analyse de la simplification lexicale et syntaxique d'une pièce de théâtre surtitrée à l'intention des sourds et malentendants
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CALL-SLT and French as Foreign Language learning: Assessment in the field of asylum-seekers and refugees
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In: 5th International Conference on Second Language Studies P. 23 (2019)
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Differences between SMT and NMT Output - a Translators' Point of View
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In: The Second Workshop on Human-Informed Translation and Interpreting Technology (HiT-IT 2019) (2019)
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Surveying the potential of using speech technologies for post-editing purposes in the context of international organizations: What do professional translators think?
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In: Proceedings of Machine Translation Summit XVII. Volume 2: Translator, Project and User Tracks pp. 149-158 (2019)
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