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Google's neural network learns to translate languages it hasn't been trained on

Frumious Bandersnatch

To be honest, the Japanese doesn't look too bad, though as it's a single long run-on sentence, it's hard to deal with anaphoric references. That aside, it appears that the only real problem with the final translation is not knowing what to do with 使いやすい and 簡単に, which both get translated to "easily".

This, surely is an artefact of focusing on collocation data. On the one hand, I think that this is a very sensible approach to translation between language pairs (eg 彼は背が高い versus "he is tall"), but on the other, the more hops you take through intermediate languages, the more it becomes a case of Chinese whispers. Once you start stringing together the little islands that make up sensible, mutually intelligible utterances without any reference to the underlying semantics, you're bound to end up with an archipelago where the first and last island will definitely not be mutually comprehensible to each other.

I don't know if you speak Japanese, or if you just picked it as an intermediate language for its strangeness factor. If you do, I'm sure that you can come up with many examples where the character of each individual language and (to take a slightly Whorfian viewpoint) the cultural backdrops and implied meanings make it difficult to translate things exactly. Stuff like the differences between I shall/will vs "going to" in English or conditional + いい[のに] (or ちょっと) in Japanese, plus all the rules for ellipsis in each language and what they means, plus, obviously, things like explicit anaphora in English vs implicit topics and referents in Japanese. Handling all of that needs deep understanding of both target languages at both a linguistic and (sometimes) a cultural level, so it's no surprise that this "island hopping" leads to mutual unintelligibility at the ends of the chain.

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