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I attended the ACL talk where he presented this. While the method was reasonably well-justified, it seems clear that the data was flawed, leading to a flawed mo
by rspeer 9y ago
I attended the ACL talk where he presented this. While the method was reasonably well-justified, it seems clear that the data was flawed, leading to a flawed model, leading to a false result. The author failed to ask himself the question "what if this didn't work?".
Here's what I would identify as the main flaw: To identify the language of a centuries-old document, he trained his model on a modern multilingual text -- the Universal Declaration of Human Rights.
(A questioner in the audience asked "If you needed a document in hundreds of languages, why didn't you use the Bible?", to which he had no real answer.)
So he ran this somewhat anachronistic model and it told him that the text was a good statistical match for being in... Esperanto. He threw this prediction out on the basis that it makes absolutely no sense. You'd think this would be the first sign that the model did not fit the data.
The #2 prediction was Modern Hebrew, which of course did not exist in the 15th century, so he said "that's close enough to biblical Hebrew" and claimed that as the result.
He asked a Hebrew speaker he knew to decipher a couple of sentences based on the model. The Hebrew speaker could not actually decipher them. The author pressed on and the Hebrew speaker obligingly produced some unsatisfying guesses at sentences, which sound remarkably like sentences from unsuccessful attempts to decipher Linear B texts.
And I don't understand why anyone would so confidently report a modification of the #2-ranked prediction of the model. We might as well go ahead and say "AI confirms: the Voynich Manuscript is in ancient Esperanto!"
The much more realistic interpretation is that the Voynich text matches the statistics of none of the language samples that the model was trained to recognize, and the model is overconfident in the probabilities it outputs.
I think the fact that the method was cool must have been part of the paper's acceptance at ACL. But it does not give us a real answer about the Voynich manuscript.
- eindiran 9y agoI studied that manuscript a bit at university, and the questioner in the audience was definitely on the right track wrt the Bible being valuable as a source of training data. We trained on the pre-15th century translations of the Bible in a number of languages. Off the top of my head, there was Old Church Slavonic, Vulgate Latin, Bibilical Hebrew plus a number of other languages people had proposed over the years, but the statistics from Voynich Herbal A and Herbal B were never very similar to any of the languages. The closest fit we found was for Manchu, trained using a Manchu translation of the 'Dao de Jing' which made us hopeful for Basanik's Manchu Hypothesis or a modified Proto-Manchu hypothesis (http://www.ic.unicamp.br/~stolfi/voynich/04-05-20-manchu-theo/ http://www.ic.unicamp.br/~stolfi/voynich/04-05-20-manchu-the...) but as we dug deeper, the n-gram frequencies ended up being wildly off. Over the years, I have been more and more doubtful that the Voynich Manuscript is natural language at all. Hopefully someone will come along and prove me wrong, but I have stopped hoping that any of these headlines is the answer for quite a while.
- IntronExon 9y agoYou might enjoy this: https://postbarthian.com/2018/01/10/review-david-bentley-harts-new-testament-translation/ https://postbarthian.com/2018/01/10/review-david-bentley-har... It’s a bit off topic, but in the spirit.