An explanation of the Voynich Manuscript text

[Torsten]

Yes, you're right about y-qo occurring more often than you'd expect by chance, so I've updated my page on You are not allowed to view links. Register or Login to view.. That was drowned out in the noise.   I think it could still be handled by a state machine, with transitions from the final glyph state to the initial glyph state.

The y-qo pattern is only an example. In his paper from 2012 You are not allowed to view links. Register or Login to view. has for instance demonstrated three effects: 1. The first word in a line of a line is longer than average, 2. The second word is shorter, 3. Over the course of the line, the average word length drops. It is possible to name numerous other patterns for the VMS.

The probabilities in the tables change by small amounts from one page cluster to the nearest one.

Sorry, but small changes for page clusters didn't explain the differences between individual pages. It is even possible to describe differences between the front and back side of a single sheet. Words common on one page can be rare on the next page. See for instance the differences I have described for the first three quires You are not allowed to view links. Register or Login to view.. 

I suggested solving this by a preprocessing step.

For which reason someone should add position based rules to randomly generated words? Such a step would mean additional work has to be done. I didn't see any advantage for this effort if the text has no meaning anyway.

You can simulate the words of the VMS with a state transition diagram. This is no surprise since it is always possible to build a state transition diagram for a given set of words. But this didn't mean that a state transition diagram is a effective method to generate a text if no computer is available. As far as I can see the process you describe is a more detailed variant of Gordon Ruggs approach. The problem is that much more effort is needed to make your method work. You have to role the dices for every glyph with probabilities depending on the previous glyphs. Moreover the probabilities must change over time. Gordon Rugg has simulated this with different tables you simulate it with different transition diagrams. But this is not enough since you both have to add additional steps to your methods to explain that the text corresponds to its container. In my eyes your method is not effective enough to generate a huge amount of text manually.