Why and how the text could be Bavarian
Only a short update:

As I haven’t written anything here for a while, here’s a quick update on the Vowel Bridge Model (VBM).

I am currently working on a generator for the Vowel-Bridge Model (VBM) and have already derived a cipher that is plausible for the Middle Ages and which can describe the VMS to 80 per cent. A small part of the cipher is still missing (particularly the LAAFU effects).

I can generate texts that come near to the VMS, but that isn't enough for me. Sometimes the various entropies were right, sometimes the Zipf curve, sometimes the word lengths, sometimes the repetition rates and the hapax rates, etc., but taken all together, it somehow fell short.

What is certain is that, among the best-known European languages, MHD / Bavarian, when used with the VBM, provide the best fit for the Voynich Manuscript.

And then I realised that the VBM is highly text-sensitive. Different texts produce very different results when run through the same generator. The hapax rate alone varies significantly from text to text.

So at the moment I’m trying to see whether the values can be optimised by adapting the text to the VBM in relation to the Voynich manuscript.

I’ve been pondering for some time whether this is a valid approach, but actually it’s quite clear: we don’t know which text lies at the heart of the matter; if the text can have such a strong impact when encoded in a cipher, then naturally one must also select a suitable text.

I hope the logic is accepted Wink.

Because it is, after all, a proof of concept based on the question: Is it possible, using the VBM and a cipher typical of the Middle Ages, to generate a VMS text that can reproduce a large proportion of the characteristics typical of VMS? That would thus prove that VMS can be based on plaintext.

No more, no less.

At this stage, I can say: yes, that is probably possible. But as for how close I’ll get to that.... 

I’m working on it... Wink
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RE: Why and how the text could be Bavarian - by JoJo_Jost - 20-08-2026, 06:22 AM

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