Can We Catch Bad Translations Automatically?
Machine translation is great when it works, but it fails often and in unpredictable ways. What causes bad machine translations and can we catch the resulting issues? What about bad human translations?
Providers and enterprises like Unbabel, Microsoft, Amazon and eBay use "quality estimation", the automatic prediction of translation quality and risk, to:
- Estimate post-editing effort
- Safely auto-approve raw machine translation for as many segments as possible
- Focus LQA
In this webinar we discuss how this technology works and how reliable it is. We will also cover where can you get this technology and how can you integrate it into your workflow today.
Host organization: ModelFront
Adam is CEO and co-founder at ModelFront. ModelFront provides translation risk prediction. He is a language learner and software engineer with experience at Google Translate as well as Adobe, Google Play and startups. Beyond translation, his interests include input correction, language identification, transliteration and synthetic data generation.