Also known as: MTPE
Definition
Machine Translation Post-Editing (MTPE), also called PEMT, is a hybrid translation workflow where raw machine translation output is reviewed and corrected by professional human linguists to achieve publication-quality results. There are two industry-standard levels: light post-editing produces text that is accurate and understandable, typically for internal or low-visibility content, while full post-editing produces output indistinguishable from human translation, suitable for client-facing and published materials. MTPE is significantly faster and less expensive than full human translation from scratch — typically 30-50% cheaper with 40-70% faster turnaround — making it ideal for large-volume technical documentation, knowledge bases, support content, and product catalogs where speed and cost matter alongside quality. The trade-off is that MTPE is less appropriate for creative, marketing, or brand-critical content where the nuance, cultural adaptation, and creative choices of full human translation remain superior.
Quick Facts
The distinction between light and full post-editing is defined by ISO 18587 and determines the quality level of the final deliverable. Light post-editing focuses on making machine translation output accurate, understandable, and free from critical errors, without rewriting for style, fluency, or native-sounding phrasing. Sentences may read somewhat machine-like but contain correct information. Light post-editing is appropriate for internal documents, knowledge base articles for search and reference, product catalog entries where users skim rather than read deeply, and high-volume content where cost and speed matter more than polish. Full post-editing produces output indistinguishable from human translation, with full stylistic adaptation, cultural localization, terminology consistency, and native-sounding phrasing. Full post-editing is appropriate for customer-facing marketing content, user-facing product documentation, training materials, and any content representing the brand to external audiences. The cost differential between light and full post-editing is typically 20-30%, with full post-editing approaching but rarely exceeding traditional human translation prices.
MTPE fits best when source content is technical, repetitive, and well-structured; when large volumes are involved (typically 50,000+ words per project or per month); when timeline pressure requires faster turnaround than traditional human translation; when the target audience will skim or reference the content rather than read it deeply; and when the content has limited brand or creative impact. Full human translation remains the better choice when source content is creative, persuasive, or emotional such as marketing copy, advertising, and brand content; when cultural nuance, idiomatic phrasing, or creative adaptation matters; when legal, medical, or regulatory content carries liability risk; when translating into languages with limited machine translation quality (some minority languages have MT quality too low for efficient post-editing); and when volumes are small enough that the overhead of setting up MT workflows outweighs benefits. Good localization vendors recommend the right mix for each project and language pair rather than defaulting to one approach.
High-quality MTPE depends on three factors: the underlying machine translation engine, the post-editor's skill, and the quality assurance process. Modern neural MT engines (DeepL, Google, Microsoft, and custom-trained engines) produce substantially better raw output than statistical MT of the past, making post-editing more productive and the final quality higher. However, MT quality varies significantly by language pair — European language pairs like English-Spanish or English-German produce very high raw quality, while English to Japanese, Korean, or minority languages requires substantially more post-editing effort. Post-editors need specific training beyond traditional translation skills to recognize and efficiently correct MT-specific errors like over-literal translations, gender disagreement in languages with grammatical gender, inconsistent terminology across long documents, and subtle meaning distortions that sound plausible but contradict the source. Leading MTPE vendors use two-tier review (post-editor plus senior linguist), CAT tool QA checks for terminology and formatting, and periodic back-translation sampling for quality verification, producing consistent results measurable against defined quality standards.
Step-by-Step
Assess source content to determine if MTPE is appropriate (volume, type, target audience).
Choose the best MT engine for the language pair (DeepL, Google, Microsoft, custom).
Process source content through the selected MT engine to produce raw output.
Human linguist edits the MT output to the agreed level (light or full) per ISO 18587.
Automated checks for terminology consistency, tags, numbers, and formatting.
Senior linguist reviews post-edited content for final quality before delivery.
Final files delivered with any required project reports and TM updates.
Key Terminology
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