Hypervector Analysis of the Voynich Manuscript

[MichelleL11]

It is interesting to see how language groups flowed out fairly naturally from the data, in groupings that one might expect. There are almost always ways to tweak an algorithm to improve it, but this is a promising start.

Oh, absolutely - l agree.  But here’s the thing - the reason why this technology was used wasn’t to get groupings of languages - it was to develop vectors to describe each language and then feed back sentence length data to find a match.  This use worked well, with known languages and using trigrams (or more, the data went up to 5-grams) they got ~97% matches.

But if it is to be used to find meaningful groupings, as was done here, a better understanding of what is actually being compared is needed.  There are acknowledged “outliers.”  Also, each vector set is built from the ground up and (understandably) Darrin didn’t show that this set “works” to be able to match new data to the known languages used.  That would be helpful to judge the functionality of the particular individual language vectors set that was built this time.

This is completely aside to all the transliteration issues (e.g. the seeming need for a meaningful alphabet to truly be able to use this technology for comparisons).

None of this is meant to discourage - just to understand better what was done, how it can be interpreted, and what experiments might make sense if Darrin wants to undertake them.