Automated Quality Estimation (AQE) and Automated Post-Editing (APE)

Techniques to Assess and Improve MT Output in the Post-Localization Era

Gain critical insights with this comprehensive 43-page report.

📘 Buy the report for $990 or choose the bundle option with two additional reports for $1,200.

Bundle Includes:

Purchase the report Purchase the bundle

Optimize Your Machine Translation Workflow

As companies push for automation, automated quality estimation (AQE) and Automated Post-Editing (APE) are gaining traction to streamline machine translation (MT) processes and reduce human post-editing. AQE scores translation accuracy, while APE refines translations using automation including large language models (LLMs). These tools promise efficiency gains, but success depends on strategic implementation, strong linguistic assets, and careful workflow integration.

This report provides a clear roadmap to determine where, when, and how to integrate AQE and APE effectively. Learn how to assess ROI, optimize workflows, and avoid common pitfalls.

Purchase the report

Key Takeaways

Practical strategies to balance automation with human oversight and control.

Why these tools aren’t a one-size-fits-all solution—and how to make them work for you.

How to assess ROI and streamline integration into existing workflows.

Where, when, and how to implement AQE and APE for maximum impact.

Why Now?

AI-driven automation is reshaping localization and translation workflows but executive pressure to implement AI everywhere can lead to missteps. This report helps you make informed decisions on selecting the right content and workflows to prove value. In some cases, refining MT engines or combining AQE with human post-editing may be better approaches.