Traduction automatique et traduction institutionnelle : le modèle neuronal a-t-il changé la donne ?

Author:

Rossi Caroline1,Talbot Aurelien1

Affiliation:

1. Université Grenoble Alpes

Abstract

A sequel to our study of the uses and perceptions of machine translation and post-editing within the European Commission’s Directorate-General for Translation (Rossi et al. 2019), this article sets out to reconsider the implications of the shift to neural machine translation in this institution. On the basis of semi-directed interviews conducted in March 2022 with 11 translators in different language department of the D-G Translation, we outline a set of concomitant factors likely to account for the transformations underway, calling into question the boundaries between machine translation and computer-assisted translation, and between translation and post-editing. 

Publisher

Fondazione Università Ca’ Foscari

Reference22 articles.

1. Uses and perceptions of Machine Translation at the European Commission;Rossi, C. ,2019

2.  Multidimensional assessment of the eTranslation output for English–Slovene ;Arnejšek, M. ,2020

3.  Resistance and accommodation: factors for the (non-) adoption of machine translation among professional translators ;Caldwell, P. ,2018

4.  Human factors in machine translation and post-editing among institutional translators ;Cadwell, P.,2016

5. IA: le test de la déférence 1;Chauvier, S.,2023

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