The final verdictĭuolingo will only work for texts for which accurate and elegant translation is not critical, and only if it’s capable of retaining massive numbers of advanced learners. If I’m right, this makes a professional quality translation uncertain, unless there was at least one professional quality version for each sentence in the database – and that’s unlikely. That’s what they did in the German example above (in Figure 1) – which must have had the professional version entered as a learner’s input. Then they hope learners, by voting, will end up getting the final version right. So what’s happening here? My guess is that the system gets machine translation as the reference on which to base its automatic feedback. My first attempt (in Figure 2) also got disappointing feedback, but when I entered it into the Google Translate version, it got “94% agreement with correct solutions from others”. But my example shows a translation equivalent to one done by a machine. The first indeed shows a translation equivalent to a professional. It is by clients paying for these learner’s translations that Duolingo will make money.īelow are two examples, one that featured in von Ahn’s Ted Talk and the second from my own own test-drive. Once learners make some progress, they are asked to participate with real texts in real translation projects. Duolingo offers a third way, with translation as a by-product of language learning – making it notionally almost as cheap as if done by machines and almost as good as if by professionals. The other half of the Duolingo project is translation.įor translating the web, machine translation is not good enough and relying only on professional translators is far too expensive. Is it as good as the leading language learning software as promised? It is good, but lacks many of the bells and whistles available in others: audiovisual context ( BBC Languages), speech recognition and synthesis ( Rosetta Stone), use of virtual words ( Avatar English), native-to-learner interaction, not just peer-to-peer ( Livemocha). The program also allows learners to review and look at how other learners have translated text, which can help with understanding their own translations.īut the program also makes mistakes, and the more you advance, the more you notice them, which can be frustrating. Translation gives the learner control over the process and a sense of achievement – translating words is often easier than dealing with lots of interaction, especially if you’re a beginner.ĭuolingo also uses gamification to great effect and always gives immediate, automated feedback and points.
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