Jälkeenkuvauksen

Jälkeenkuvauksen, often translated as post-editing, is a term used in translation studies and practice to describe the process of reviewing and revising a machine-translated text to meet specific quality standards. It involves human translators or editors working on the output of machine translation (MT) systems, such as Google Translate or DeepL, to correct errors, improve fluency, ensure accuracy, and adapt the translation to the target audience and purpose.

The level of post-editing can vary. Light post-editing focuses on fixing only the most critical errors that prevent comprehension, aiming for a usable but not necessarily polished translation. Full post-editing, on the other hand, involves a more thorough revision to achieve a level of quality comparable to human-only translation, addressing stylistic issues, idiomatic expressions, and cultural nuances.

The rise of neural machine translation (NMT) has significantly improved the quality of raw MT output, making post-editing a more viable and efficient workflow for many translation projects, especially those requiring high volumes or quick turnaround times. It can offer cost and time savings compared to traditional human translation, provided the source text is suitable for MT and the post-editing process is well-managed. However, the effectiveness of post-editing depends on the quality of the MT output, the skill of the post-editor, and the defined quality requirements for the final translation.