MT or not MT? Do translation specialists know a machine-translated text when they see one?

Rudy Loock; Nathalie Moulard; Quentin Pacinella

MT or not MT? Do translation specialists know a machine-translated text when they see one?

Rudy Loock, Nathalie Moulard, Quentin Pacinella

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Abstract

In this article, we investigate translation specialists’ capacity to identify raw machine translation (MT) output in comparison with so-called “human” translations produced without any use of MT. Specifically, we measure this capacity via an online activity, based on different criteria: (i) degree of expertise (translation students vs. professionals with at least 5 years’ experience), (ii) MT engine (DeepL, Google Translate, Reverso, ChatGPT), and (iii) length of input (1-3 sentences). A complementary, qualitative analysis, based on participants’ feedback, provides interesting insight on how they discriminate between raw MT output and human translations.

Anthology ID:: 2025.mtsummit-1.35
Volume:: Proceedings of Machine Translation Summit XX: Volume 1
Month:: June
Year:: 2025
Address:: Geneva, Switzerland
Editors:: Pierrette Bouillon, Johanna Gerlach, Sabrina Girletti, Lise Volkart, Raphael Rubino, Rico Sennrich, Ana C. Farinha, Marco Gaido, Joke Daems, Dorothy Kenny, Helena Moniz, Sara Szoc
Venue:: MTSummit
SIG:
Publisher:: European Association for Machine Translation
Note:
Pages:: 442–454
Language:
URL:: https://aclanthology.org/2025.mtsummit-1.35/
DOI:
Bibkey:
Cite (ACL):: Rudy Loock, Nathalie Moulard, and Quentin Pacinella. 2025. MT or not MT? Do translation specialists know a machine-translated text when they see one?. In Proceedings of Machine Translation Summit XX: Volume 1, pages 442–454, Geneva, Switzerland. European Association for Machine Translation.
Cite (Informal):: MT or not MT? Do translation specialists know a machine-translated text when they see one? (Loock et al., MTSummit 2025)
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PDF:: https://aclanthology.org/2025.mtsummit-1.35.pdf

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@inproceedings{loock-etal-2025-mt,
    title = "{MT} or not {MT}? Do translation specialists know a machine-translated text when they see one?",
    author = "Loock, Rudy  and
      Moulard, Nathalie  and
      Pacinella, Quentin",
    editor = "Bouillon, Pierrette  and
      Gerlach, Johanna  and
      Girletti, Sabrina  and
      Volkart, Lise  and
      Rubino, Raphael  and
      Sennrich, Rico  and
      Farinha, Ana C.  and
      Gaido, Marco  and
      Daems, Joke  and
      Kenny, Dorothy  and
      Moniz, Helena  and
      Szoc, Sara",
    booktitle = "Proceedings of Machine Translation Summit XX: Volume 1",
    month = jun,
    year = "2025",
    address = "Geneva, Switzerland",
    publisher = "European Association for Machine Translation",
    url = "https://aclanthology.org/2025.mtsummit-1.35/",
    pages = "442--454",
    ISBN = "978-2-9701897-0-1",
    abstract = "In this article, we investigate translation specialists' capacity to identify raw machine translation (MT) output in comparison with so-called ``human'' translations produced without any use of MT. Specifically, we measure this capacity via an online activity, based on different criteria: (i) degree of expertise (translation students vs. professionals with at least 5 years' experience), (ii) MT engine (DeepL, Google Translate, Reverso, ChatGPT), and (iii) length of input (1-3 sentences). A complementary, qualitative analysis, based on participants' feedback, provides interesting insight on how they discriminate between raw MT output and human translations."
}

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%0 Conference Proceedings
%T MT or not MT? Do translation specialists know a machine-translated text when they see one?
%A Loock, Rudy
%A Moulard, Nathalie
%A Pacinella, Quentin
%Y Bouillon, Pierrette
%Y Gerlach, Johanna
%Y Girletti, Sabrina
%Y Volkart, Lise
%Y Rubino, Raphael
%Y Sennrich, Rico
%Y Farinha, Ana C.
%Y Gaido, Marco
%Y Daems, Joke
%Y Kenny, Dorothy
%Y Moniz, Helena
%Y Szoc, Sara
%S Proceedings of Machine Translation Summit XX: Volume 1
%D 2025
%8 June
%I European Association for Machine Translation
%C Geneva, Switzerland
%@ 978-2-9701897-0-1
%F loock-etal-2025-mt
%X In this article, we investigate translation specialists’ capacity to identify raw machine translation (MT) output in comparison with so-called “human” translations produced without any use of MT. Specifically, we measure this capacity via an online activity, based on different criteria: (i) degree of expertise (translation students vs. professionals with at least 5 years’ experience), (ii) MT engine (DeepL, Google Translate, Reverso, ChatGPT), and (iii) length of input (1-3 sentences). A complementary, qualitative analysis, based on participants’ feedback, provides interesting insight on how they discriminate between raw MT output and human translations.
%U https://aclanthology.org/2025.mtsummit-1.35/
%P 442-454

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Markdown (Informal)

[MT or not MT? Do translation specialists know a machine-translated text when they see one?](https://aclanthology.org/2025.mtsummit-1.35/) (Loock et al., MTSummit 2025)

MT or not MT? Do translation specialists know a machine-translated text when they see one? (Loock et al., MTSummit 2025)

ACL

Rudy Loock, Nathalie Moulard, and Quentin Pacinella. 2025. MT or not MT? Do translation specialists know a machine-translated text when they see one?. In Proceedings of Machine Translation Summit XX: Volume 1, pages 442–454, Geneva, Switzerland. European Association for Machine Translation.