Towards robotic translation?

The appearance on the web in 2017 of new translation services based on “deep learning” artificial intelligence algorithms such as DeepL and Google Translate corresponded to a new leap forward in machine translation. These recent systems, like the previous generation of statistical machine translation and factored machine translation, rely on large aligned corpora and produce results whose quality is in some cases comparable to some human translations. It follows that to produce added value, the translator must provide something extra compared to the machine. This added value may be inherent in fields where the use of machines is not in itself of much interest because of the essentially aesthetic dimension of translation: this is the case for the translation of certain literary genres. Although much academic translation research refers to this field, it represents only a small fraction of the existing professional translation activity.

As the machine allows productivity gains of 150 to 200% (some translators reach outputs of 6,000 to 8,000 words per day), the post-editing technique is becoming increasingly important in the language industries, as confirmed in 2017 by the introduction of the ISO 18587 standard “Translation services — Post-editing of machine translation output — Requirements”. Post-editing poses a moral dilemma for translators: accepting that the machine, and not them, is the source of their own translation.

Artificial intelligence is changing our professional activities and translation is one of the fields showing such changes. This issue brings together articles that do not aim to take stock, but rather to present reflections and practical experience not only from professional translators but also from academics specialising in teaching and/or researching translation. The rapid development of artificial intelligence is forcing not only professional translators but also translation courses to adapt. The approaches put into dialogue in this volume concern translation, but also natural langage processing, linguistics, translation studies and language teaching.

The volume comprises the articles below. Links to the final versions will be added as they become available.

Volume edited by Anne Baillot (Le Mans Université, France), Ellen Carter, Thierry Grass and Pablo Ruiz Fabo (Université de Strasbourg, France). The articles were peer-reviewed by members of the scientific committee of the Robotrad 2021 conference or by external reviewers. We thank all reviewers for their work.


a. Vers une robotique du traduire – Introduction. Anne Baillot ; Ellen Carter ; Thierry Grass ; Pablo Ruiz Fabo. 

b. Towards robotic translation?⁠ – ⁠Introduction. Anne Baillot ; Ellen Carter ; Thierry Grass ; Pablo Ruiz Fabo.

I. Historical and linguistic approaches

1. Le mépris (envers la traduction automatique) est-il une attitude traductologique ? Nicolas Froeliger

2. Contra Automata : Orgueil et préjugés ? Marc Lebon

II. Pedagogical practices

3. Traduction automatique et doublage : impressions d'une expérience d'enseignement. Julio de los Reyes Lozano

4. The use of MT by undergraduate translation students for different learning tasks. Joop Bindels ; Mark Pluymaekers

5. Source or target first? Comparison of two post-editing strategies with translation students. Lise Volkart ; Sabrina Girletti ; Johanna Gerlach ; Jonathan David Mutal ; Pierrette Bouillon

III. Biotranslation vs. Machine Translation

6. Biotraduction versus traduction automatique : la subjectivité en question. Maryam Alrasheed

7. DeepL et Google Translate face à l'ambiguïté phraséologique. Françoise Bacquelaine

8. Le projet OPTIMICE : une optimisation de la qualité des traductions de métadonnées par la collaboration entre acteurs du monde scientifique et traduction automatique. Katell Hernandez Morin ; Franck Barbin

9. Ghosts in the machine: Can adaptive MT help reclaim a place for the human in the loop?. Hanna Martikainen

IV. Challenges for professional translation

10. Some Reflections on the Interface between Professional Machine Translation Literacy and Data Literacy. Ralph Krüger

11. Vers une évaluation empirique des textes traduits et de la qualité en traduction. Éric Poirier

12. Le traducteur automatique comme outil du traducteur indépendant spécialisé en médecine. Magali Vidrequin

13. La traduction littéraire automatique : Adapter la machine à la traduction humaine individualisée. Damien Hansen. 

14. Machine Translation and Gender biases in video game localisation: a corpus-based analysis. María Rivas Ginel ; Sarah Theroine

VI. Feedback from professional translators

15. DeepL résout-il les conflits ? Bio-traduire et post-éditer les courriers d'avocats de l'italien en français. Alain Volclair

16. Dan Brown et Patricia Cornwell à l'épreuve de DeepL. Dominique Defert

17. Voyage au bout de la traduction automatique. Jean-Yves Bassole