Machine translation post-editing (MTPE / post-editing)
Description
MTPE combines the speed of neural machine translation (NMT) with the precision of human editing. After an engine – such as Language Weaver – generates a translation, linguists refine the content for grammar, meaning and style.
Post-editing can range from light (minor corrections to improve readability) to full (comprehensive revision to match human translation quality). The choice depends on project goals, target audience and required quality level. MTPE helps organizations reduce turnaround times while maintaining high standards. It also improves the underlying MT system – human edits provide valuable feedback that retrains and refines custom engines over time.
Example use cases
- Localization: Accelerate multilingual content production while maintaining brand tone.
- Documentation: Edit MT output for accuracy and compliance in regulated industries.
- Support: Ensure automated translations are clear and trustworthy.
- E-commerce: Localize product data and marketing content rapidly.
- Training: Create high-quality reference translations to improve MT model performance.
Key benefits
RWS perspective
At RWS, machine translation post-editing is how we balance human insight with AI scale. Through Language Weaver and Trados, linguists work within secure, connected environments where machine-generated translations can be refined efficiently and consistently.
Our Human + Technology model empowers editors to focus on creativity and nuance while automation handles repetition and formatting. Clients can define custom MTPE guidelines – from light to full post-editing – depending on their goals, content type and quality expectations. Combined with analytics, MTPE becomes part of a continuous improvement loop that strengthens both human and machine performance.