27-06-2025, 01:40 AM
(26-06-2025, 08:05 AM)Mauro wrote: You are not allowed to view links. Register or Login to view.(26-06-2025, 01:47 AM)ReneZ wrote: You are not allowed to view links. Register or Login to view.I have often wondered about the initialisation method. After all, the self-citation explains (in a way) how to set up the 'next' word from a previous section, but I never saw anything about how to start.
The seed sentence is in the 'metadata' at the top of Torsten's output files. For the one posted on GitHub:
Quote:#text.initial_line=pchal shal shorchdy okeor okain shedy pchedy qotchedy qotar ol lkar
Note: actually the last two words 'ol lkar' are then not used in generating the text, I don't know why the sentece is truncated, maybe a bug, but it's not important for the successive elaboration.
(26-06-2025, 01:47 AM)ReneZ wrote: You are not allowed to view links. Register or Login to view.Another thing I have been curious about is how the most frequent words come about.
There are probabilty parameters inside the software. Ie. this instruction (file You are not allowed to view links. Register or Login to view.):
Quote:{{"k"} , { new Substitution( new String[] {"t"}, 77), new Substitution(new String[] {"p"}, 94), new Substitution(new String[] {"f"}, 100)}},
I think it determines what can be substituted for 'k': I guess 77% of times with 't', (94-77)= 17% of times with 'p' and the remaining times with 'f'.
I think a human being would behave more of less the same way, just with greater fuzziness, and with the 'parameters' varying in time.
Thanks!
Now these are the 'rules' for the text generated by the app.
These would be a model for the original Voynichese text in the MS.
Howevever, how does the real text behave?
That it is different for a few different sections isn't a major problem in my opinion, especially if there were indeed several scribes, whose roles may have been more than just copying...

