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La plus-value de la biotraduction face à la machine
5 references·0 citing·23 second hop
La plus-value de la biotraduction face à la machine (2019)La plus-value de la biotraduction face à …impact of Google Neural Machine Translation on Post-editing by student translators (2019)impact of Google Neural Machi…What to expect from Neural Machine Translation: a practical in-class translation evaluation exercise (2018)What to expect from Neural Ma…Translationese and Post-editese: How comparable is comparable quality? (2018)Translationese and Post-edite…Machine learning: Implications for translator education (2017)Machine learning: Implication…La traductologie de corpus (2016)La traductologie de corpusCorpus Linguistics and Translation Studies — Implications and Applications (1993)Cohesion in English (2014)Corpus Linguistics and Translation Studies* (2019)Towards a machine learning approach to the analysis of indirect translation (2021)Post-Editese in Literary Translations (2022)The role of deliberate practice in the acquisition of expert performance. (1993)The Routledge Handbook of Strategic Communication (2014)Corporate Communication: A Guide to Theory and Practice (2020)Fair MT (2020)The role of machine translation in translation education: A thematic analysis of translator educators’ beliefs (2022)University students’ perceptions of using generative AI in translation practices (2025)Competence-based Curriculum Design for Training Translators (2007)A Productivity Test of Statistical Machine Translation Post-Editing in a Typical Localisation Context (2010)Translation as human–computer interaction (2012)No more rage against the machine: how the corpus-based identification of machine-translationese can lead to student empowerment (2020)What has changed with neural machine translation? A critical review of human factors (2021)Using DeepL translator in learning English as an applied foreign language – An empirical pilot study (2023)The language-as-fixed-effect fallacy: A critique of language statistics in psychological research (1973)Predicting student translators’ performance in machine translation post-editing: interplay of self-regulation, critical thinking, and motivation (2020)Machine translation literacy and undergraduate students in applied languages: Report on an exploratory study (2021)Towards a Corpus-based, Statistical Approach to Translation Quality: Measuring and Visualizing Linguistic Deviance in Student Translations (2018)Translanguaging and Multilingual Academic Literacies: How Do We Translate That into French? Should We? Pour en faire quoi ? (et pourquoi s'en faire?) (2020)Language Policy and Planning (2024)
this work references cited by second hop

References

  • 2018What to expect from Neural Machine Translation: a practical in-class translation evaluation exercise106 cited
  • 2016La traductologie de corpus89 cited
  • 2019impact of Google Neural Machine Translation on Post-editing by student translators74 cited
  • 2017Machine learning: Implications for translator education46 cited
  • 2018Translationese and Post-editese: How comparable is comparable quality?31 cited

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