What is machine translation post-editing (MTPE)?
Machine Translation Post-Editing (MTPE) is a workflow where machine-generated translation is reviewed and refined by a qualified human linguist to achieve the required quality standard. MTPE combines AI speed with human quality for cost-effective results.
Detailed description
Machine Translation Post-Editing (MTPE) is a workflow where machine-generated translation is reviewed and refined by a qualified human linguist to achieve the required quality standard. It combines the speed and cost efficiency of machine translation with human expertise to produce output that is accurate, fluent, and fit for purpose.
MTPE operates at two levels. Light post-editing focuses on correcting critical errors (mistranslations, omissions, and factual inaccuracies) while accepting that the output may not achieve the same stylistic polish as full human translation. It is appropriate for content where accuracy matters but publication quality is not required, such as internal communications or knowledge base articles. Full post-editing brings machine translation output to the same quality standard as human translation, addressing not just accuracy but also fluency, style, terminology consistency, and cultural appropriateness. It is appropriate for any content that will be published or distributed to external audiences.
MTPE is most effective for content types where machine translation engines perform well: typically factual, structured content with consistent terminology. It is less effective for creative content, marketing copy, or highly nuanced material where the machine translation baseline is poor and extensive rewriting negates the efficiency gains.
The economics of MTPE depend on the quality of the raw machine output. When MT quality is high, post-editing is significantly faster and more cost-effective than translation from scratch. When MT quality is poor, post-editing can actually take longer than human translation because the editor must identify and correct errors while being influenced by the machine's choices.
LEXIGO offers MTPE as part of our service portfolio, recommending it where the content type, quality requirements, and MT engine performance make it an efficient and appropriate approach.
Why it matters
MTPE offers a middle ground between raw machine translation (fast and cheap but unreliable) and full human translation (high quality but more time and cost). For organisations with large content volumes and mixed quality requirements, MTPE enables a tiered approach: investing in full human translation for high-visibility content while using MTPE for content where speed and cost are the priority.
Understanding when MTPE is appropriate versus when full human translation is needed helps organisations optimise their translation budget without compromising quality where it matters most.
Related questions about machine translation post-editing
What does MTPE stand for?
MTPE stands for machine translation post-editing: a qualified linguist reviews and corrects machine translation output until it meets the quality you agreed.
What is HT and MTPE?
HT is human translation, where a translator writes the translation from scratch. MTPE starts with machine output that a linguist then edits. HT suits official, legal, clinical and creative content; MTPE can suit high-volume, lower-risk content.
What is the difference between light and full post-editing?
Light post-editing fixes errors in meaning so the text is understandable, without polishing style. Full post-editing aims for a result comparable to human translation. The ISO 18587 standard sets requirements for full post-editing.
Does LEXIGO offer MTPE?
Yes, as one option. It depends on the option you choose: LEXIGO offers different options for different use cases, from fully human NAATI certified translation to AI built into our secure translation technology plus linguist review. Certified, legal and clinical content is always human translated.
When is MTPE suitable?
MTPE suits high-volume content such as internal material, knowledge bases or product data, where speed matters and a trained linguist reviews the output. It is not suitable for certified documents or content with legal, clinical or financial weight.