HMM automatic vowel detection

[ReneZ]

The Hidden Markov Model is a general method for analysing sequences (to put it simply).

One of many applications is language expressed as a sequence of characters.
For a language that has reasonably clear vowel-consonant alternation, a two-state HMM will tend to split the characters into a class of vowels and a class of consonants.

It's therefore worth applying a two-state HMM to the Voynich text.
Since the algorithm doesn't really know about vowels and consonants, it is unbiased.
In a way, it isn't going to force the identification of vowels and consonants if there aren't any (and even if the symbols o, a, i "look like" vowels).

The fact that it returns position-dependent states tells us that the Voynich text is "different".

That's the first step. A negative result, but one that at least fits with the observation that all people who have tried to turn the VMS text into Latin by simple substitution (and are still trying) have failed.

The next step can go in many directions:
- try more states
- play around with the text to see if there is something that makes the HMM return vowels and consonants
- both of the above
- see if there is other text that behaves like the VMS