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As a case in point, some translation agencies and translators even distinguish between \u201clight post-editing (LPE)\u201d and \u201cfull post-editing (FPE).\u201d In their view, LPE focuses solely on comprehensibility, fixing critical errors to make the text understandable, while FPE ensures the text is accurate, coherent, and stylistically appropriate, claiming it to be indistinguishable from human translation. While it is debatable that FPE is as high quality as a human translation, it is safe to say that if you really want a subpar translation, you can just ask for LPE.<\/p>\n
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To argue that FPE is also lower quality than a \u201chuman-first\u201d translation, you could say that MTPE is similar to using AI to draft a text. When you prompt an AI agent to create a text or generate ideas, you are not creating original content. AI is simply regurgitating concepts and points of view that it gleans from existing texts. In the same way, a translator who uses NMT or an LLM to make a first pass at translating a sentence or passage is simply regurgitating past translations, and is not creating anything original. The translation, as a result, comes out flat, even though it may be accurate.<\/p>\n
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This is not to say that NMT and LLMs have no place in the translation process. Studies such as this one<\/a>[2]<\/a> and this one<\/a>[3]<\/a> evaluate the quality of translation between artificial intelligence translation and human translations and show that the highest quality translation is produced when a translator interacts with translation tools to refine their translation. This is because the translator is generally more engrossed in the translation process as they translate sentence by sentence or paragraph by paragraph, sometimes looking ahead in the text as they translate to gain clarity and get more context. Conversely, with MTPE, a translator must \u201clook behind\u201d in the translation to ensure that translations are consistent, but can they say with certainty that the proposed translation was the best translation from the start? It is not a given, especially when under time constraints. \u00a0<\/p>\n <\/p>\n As the classic Venn diagram shows, if you want it fast and cheap, you\u2019ll sacrifice quality. Giving translators more time and the freedom to translate from scratch ensures that you\u2019ll get a translation that is not only accurate, but also original. <\/a><\/p>\n <\/p>\n [1]<\/a> Moneus, Ahmed Mohammed and Yousef Sahari, \u201cArtificial intelligence and human translation: A contrastive study based on legal texts,\u201d Heliyon<\/em>, Vol. 10, Issue 6e28106 (2024), https:\/\/www.cell.com\/heliyon\/fulltext\/S2405-8440(24)04137-9, Accessed Jan 30, 2026.<\/p>\n [2]<\/a> Fu, Lingling and Lei Liu, \u201cWhat are the differences? A comparative study of generative artificial intelligence translation and human translation of scientific texts,\u201d Humanities and Social Sciences Communication<\/em>, 11, 1236 (2024), https:\/\/www.nature.com\/articles\/s41599-024-03726-7<\/a>, Accessed Jan 30, 2026.<\/a><\/p>\n [3]<\/a> Shahmerdanova, Roya, \u201cArtificial Intelligence in Translation: Challenges and Opportunities,\u201d Acta Globalis Humanitatis et Linguarum, Vol. 2, No. 1 (2025), https:\/\/egarp.lt\/index.php\/aghel\/article\/view\/105<\/a>, Accessed Jan 30, 2026\u00a0\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":" Avez-vous d\u00e9j\u00e0 \u00e9t\u00e9 tent\u00e9 de traduire un document en utilisant un moteur de traduction, tel que Google Translate ou DeepL ? Voyons pourquoi cette fa\u00e7on de faire n\u2019est pas une bonne id\u00e9e, si vous voulez un texte qui r\u00e9sonne avec votre public cible.<\/p>","protected":false},"author":7,"featured_media":13688,"comment_status":"open","ping_status":"open","sticky":true,"template":"","format":"standard","meta":{"_acf_changed":false,"_seopress_robots_primary_cat":"none","_seopress_titles_title":"%%sitetitle%% %%post_title%% %%post_excerpt%%","_seopress_titles_desc":"Ever been tempted to draft a translation using a translation engine such as Google Translate or DeepL? Let\u2019s break down why that\u2019s not a good idea if you want a text that resonates with your target audience. %%post_excerpt%%","_seopress_robots_index":"","footnotes":""},"categories":[165,166,141,163],"tags":[],"class_list":["post-13685","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-artificial-intelligence","category-machine-translation","category-post-editing"],"acf":[],"_links":{"self":[{"href":"https:\/\/wordstyle.ca\/fr\/wp-json\/wp\/v2\/posts\/13685","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wordstyle.ca\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wordstyle.ca\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wordstyle.ca\/fr\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/wordstyle.ca\/fr\/wp-json\/wp\/v2\/comments?post=13685"}],"version-history":[{"count":5,"href":"https:\/\/wordstyle.ca\/fr\/wp-json\/wp\/v2\/posts\/13685\/revisions"}],"predecessor-version":[{"id":13696,"href":"https:\/\/wordstyle.ca\/fr\/wp-json\/wp\/v2\/posts\/13685\/revisions\/13696"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wordstyle.ca\/fr\/wp-json\/wp\/v2\/media\/13688"}],"wp:attachment":[{"href":"https:\/\/wordstyle.ca\/fr\/wp-json\/wp\/v2\/media?parent=13685"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wordstyle.ca\/fr\/wp-json\/wp\/v2\/categories?post=13685"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordstyle.ca\/fr\/wp-json\/wp\/v2\/tags?post=13685"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"\"](\"https:\/\/wordstyle.ca\/wp-content\/uploads\/2026\/02\/Venn-diagram-translation.jpg\"){kind=spacer}
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