Machine translation and CAT tools.
Machine translation excels at information, but literary translation demands style, voice, and culture. Human translators remain indispensable for nuan...
Choosing between CAT tools and raw machine translation? Here's a practical breakdown of speed, quality, cost, and control—and when each approach makes...
BLEU scores have dominated MT evaluation for two decades, but they lie about quality. For localization, Translation Edit Rate and post-editing effort ...
BLEU is dead. If you're still using it to judge translation quality, you're flying blind. Here's what to use instead—and why post-editing is your real...
BLEU is outdated for localization QA. Post-editing effort and neural metrics like COMET and BLEURT correlate better with human judgment and reflect re...
BLEU has been the go-to metric for machine translation for 20 years, but it's misleading. Here's what actually works and what you should use instead.
Machine translation has transformed the industry, but literary translation still demands the human touch. Here's why translators must own the process,...
That BLEU number you're chasing? It doesn't measure what you think. If you're choosing a translation tool or shipping output, you need a metric that r...
Machine translation has improved dramatically, but relying on it blindly for product localization is a mistake. Learn when to trust NMT, when to post-...
Stop treating machine translation as a one-click answer. In real localization, MT is a raw material. Here's how a working team decides when to trust i...
Think machine translation is ready for prime time? It's not. Here's how to build a post-editing workflow that actually works, with real numbers and a ...
Neural machine translation is impressive, but it's not a translator. Here's how to combine MT and CAT tools for maximum efficiency and quality, with a...