Neural translation and post-editing
Neural machine translation with human review
How neural machine translation works, the mistakes it makes and why human post-editing (MTPE) is key to a professional result.
Neural machine translation uses neural networks trained on large volumes of text to translate whole sentences in context, not word by word. It is fast and increasingly accurate, but it still fails with technical terms, humor, names and tone, so we use it as a first draft that a translator corrects.
What is post-editing (MTPE)?
Post-editing is the review a human translator performs on machine-translated text. They fix meaning errors, unify terminology and adjust tone. It is the method that combines the speed of AI with the quality of a professional translation.
Key aspects of this technology
Speed
Drafts in minutes, even for long texts.
Human post-editing
A translator fixes meaning, terms and tone.
Memory and glossary
Approved terms are reused on every project.
Frequently asked questions
What is the difference between machine translation and neural translation?
Is machine translation reliable?
What is MTPE?
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