"Je t'aime" is wrongly classified as English. (Although understandable, since it's short)

How does this work? You claim it has "zero language knowledge," so how does it classify? Did it start out with nothing, and then train it on a corpus?

EDIT: nevermind, found your slides (http://polyglossy.com/presentation.pdf [pdf]) How big of a corpus did you use?

I've used around 40KB of text per language for training.

wouldn't something like 2-gram bayes be more accurate & faster?

I don't know. I haven't really done NLP before. My guess is that it would be slower, but not by a significant amount. It might be more accurate, so I could give it a shot.

I don't think 2-gram bayes uses any NLP at all. To my understanding, it's just like naive bayes, but can use word combinations to improve accuracy. In terms of complexity, bayes classification is not much more than O(N).

Any chance of posting the source?

Yeah, I'll probably push it to github later this week.

...and here it is: https://github.com/lgeek/polyglossy (with a slight delay because I've worked on improving the accuracy)