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Traduction automatique et deep learning : mort et renaissance de la traduction spécialisée ?

Abstract : The development since the sixties of automatic translation has understandably provoked concern among professional translators, as well as LSP teachers, considering that this technique might threaten the very practice and teaching of translation. Spectacular recent improvements have only made this concern stronger. The presentation will first examine these advances to show that they are based on a combination of the integration of general language syntactic rules and an approach familiar to LSP specialists, i.e. corpus analysis. This also involves taking into account the issue of « deep learning ». We will observe the way MT specialists now try to go beyond a general language centered activity to deal with highly specialized fields, sometimes using crowdsourcing and cooperation with professionals. Based on the research work of a specialized translation master’s student, we will specifically deal with the development of a central activity for automatic translation, namely translation quality evaluation techniques, their perspectives and their limitations in dealing with lexical, syntactic, semantic and pragmatic criteria. Our conclusion will address the consequences of the accessibility of these new technologies: are we paving the way towards the death foretold of human translation, and even language learning, or shall we see the renaissance of language practice and linguistic transfers?
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Submitted on : Tuesday, May 24, 2022 - 12:13:08 PM
Last modification on : Thursday, May 26, 2022 - 3:00:25 AM


  • HAL Id : hal-03676826, version 1


Geneviève Bordet, Maud Bénard. Traduction automatique et deep learning : mort et renaissance de la traduction spécialisée ?. 60e congrès de la SAES : « RenaissanceS ». Atelier 21 – Anglais de spécialité–GERAS : Renaissance en anglais de spécialité, renaissance de l’anglais de spécialité ?, Société des Anglicistes de l'Enseignement Supérieur (SAES), Jun 2021, Tours, France. ⟨hal-03676826⟩



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