Google translate VS DeepL

As far as I know, DeepL is allowed to (and will prioritize) naturally-sounding sentences so it feeds in the extra context it received during ML model training. There are some cases where the answer is extremely specific (f.e. a name of a particular institution) which shows that the data set was oddly unbalanced.


I haven’t think of this much before, but there is a possibility of using DeepL to translate to Japanese (with a grain of salt, nonetheless).

I can’t yet find a fitting vocabulary for vocabulary hunting, though.

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