The science behind DeepL's translation quality
Text translation quality is hard to measure and easy to game. This whitepaper explains how DeepL evaluates quality using blind comparative human judgment, why established metrics like BLEU and COMET fall short, and what our benchmarking methodology actually tests.
What's inside the whitepaper
- The limits of BLEU and COMET — why fluency-oriented scores miss the errors that matter most in production
- DeepL's blind comparative evaluation methodology — how DeepL designs tests to eliminate brand, position, and familiarity bias
- How win rates are calculated — the pairwise comparison model that produces quality rankings
- Honest limits of the approach — what benchmarks do and don't tell you
Download the whitepaper
Get your copy of How DeepL Evaluates Translation Quality, to learn more about the methodology.