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Yes totally can be. Nothing English language specific about this. Scoring the models is a bit of a pain without a large corpus of English, but the training data was only 800 words.

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You said that you wrote a scoring function based on your subjective response to outputs. Supposedly if English is your native language (it seems to be) then you would have influenced the algorithm to home in on English phonology.

Surely?

I looked at about 20 words and they all seemed like decent English candidate words, including one actual English word, "molest".

The first kind of scoring function was language independent (e.g, penalize words showing up from the training set, penalize < 3 character words, penalize duplicate words, penalize common words), and the second scoring function needed a large training set of English words (but could be any other training set).

All this is described at the top. I guess you didn't read that.

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