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I think it's possible, but you would need peices to draw off of: Google uses U.N. translations to train their algorithms, but how many documents do we have tran

• danohuiginn 16y ago
  We have documents that have gone through an editing process, with changes tracked from draft through to published article. I'm thinking particularly here of the process inside, say, a news agency. Many of the changes made by sub-editors are fairly mechanical modifications, to conform to a standard style. They might well be sufficiently repetitive to train a 'translator'. You could also take a corpus of 'good' and a corpus of 'bad' writing, and compare the features in each. sentence length, constructions used. Origin of words would be an interesting one ('never use a Latinate word where an Anglo-Saxon one will do'). Unfortunately, most of the difference between good and bad writing is in the ordering of ideas; you can't really deal with that on statistical grounds.