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
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.
Adam is the CEO and co-founder at ModelFront. He is a language learner and software engineer with experience at startups, Google Translate, Google Play and Adobe. Beyond machine translation, his interests include input correction, language identification, transliteration and synthetic data generation.