A One-Page Ledger Method for Generating Voynich-Like Text

[Dunsel]

I think you may have missed my last reply because it was at the bottom of a page, but I'd also like to say here a bit about why I personally don't find this research direction interesting (I'm talking about my perspective only) in the context of Timm & Schinner.

I very well may have missed that post and my apologies for doing so.

There is nothing in my work that says it can't be a cypher.  I have mentioned in another reply that a whole production of gibberish is very unsatisfying.  I still have this underlying hope/belief that it does contain actual content.  My working theory is that it's mnemonic which you could say is a form of cypher.  The point of the generator is to explore the copy/mutate possibility. To locate the sources for these pages, the parent words, and offer a possibility.  If the sheet/quire source method I think I've discovered leads to a decipherment, I'm all in and I truly hope it helps you in that quest. Let me know what I can do to further that.  And you are correct, it may very well be a dead end. But, in my opinion, if you don't know the neighborhood the best way to find out if that street is a cul-du-sac is to actually drive down that street and look.  And so far, I am aware of methods that can produce Voynich looking text that fails statistically.  I'm trying to approach from the other end.  To succeed statistifcally and THEN match visually.

Also, you piqued my curiosity with your bigram smashing generator idea.  I actually pursued that yesterday.  I had codex create a small machine learning script that would run through my data and, instead of bigrams/trigrams, it tried to break words into syllables and create a set of weighted tables.  The thought there was, a scribe would understand pronunciation and syllables rather than linguistic terms like bigram, n-gram, etc.  And I've always had this idea that the Voynich can be pronounced. I then rearranged your generator idea using those ML results.  Here's what I got.

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chckhol qotchody okchees chal chos shody ykchckhey otshes
chody okchees oteoky chckheey ypshor oteodaiin ypshor choty
chees shor chckhol chochor chopchor shey choschochor chees
chopchol qokeeor chal chody qokeor qotchaiin qokchar cheees
cheeaiin chees shey chopydaiin chody otar okor ypshody
yshody chopchos ykchcthey shokydaiin ykchey cheeey chos chees
chckhor choky qokchol ykchey chos shody yshor chochor
otol qokchaiin qokchor shody chcthod qotchaiin qokeeoky cheeaiin
qokchol chos chochor qocthod chopchol shey qokcheey ykeees
qokchor chochor qotody okchy chodalchy shey otaiin chody
chckhey okchody chckheol chody chal chckhey shoteodaiin qotchaiin
shotar chcthol yfod chcthol chal yckhey qotchody

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ykchey yfod qotchaiin chcthaiin chckhey shoteeaiin otol qotchaiin
qokeey chcthody chckhey shes chody choty chopydaiin chckhor
shodan otchodalchy chcthor chees chocthy shey chopchey qokeey
chcthol shey ykchopchey okshor chokchol otchodalchy chopor okchal
chockhy chodalchy ykchopchey otchockhy shod chcthal chocthy qokeeodaiin
qokody chopydaiin cheees chckhey chos ykam qotchody shey
qochckhol okshor chockhody shotaiin ykeees chckhoal cheeaiin otchoty
qokodalchy chody otchoty shod cheees okeeaiin shor qokchaiin
chees qockhol chal chody ykam chees chcthaiin ykchal
qokeor qotchody qochckhol qotchaiin choty qotody chal qocthey
cheeey qokcheey qocthey chckheey yckhey qokchor chckhody qokchaiin
shor chees qokchor chckhey chopydaiin qokeaiin shod

That uses no seed page, just "syllables".  It does use a type of ledger with a lot of weighting.  So you can see, it does LOOK a lot more like Voynich than my generator. However, the statistics were WAY off.  In particular, the vocabulary size and hapax count.  I could likely have continued working on it and gotten those numbers closer to Voynich, but, it would have required some pretty serious memory juggling to produce it unless... they had a method for pronouncing Voynich words which we will likely never prove.

Code:

============================================================ GLOBAL STATISTICS ============================================================ Tokens                : 9500 Types                  : 379 TTR                    : 0.0399 Hapax                  : 59 Chunk uses            : 24337 Chunk types used      : 271 Word length distribution 4  1830 5  1239 6  1622 7  2159 8  1520 9  791 10  211 11  127 12  1 Top 30 words chody          383 shey            358 chckhey        310 cheees          298 chos            293 shor            271 chees          211 qokchor        209 chal            168 chckhol        165 qokeey          160 shody          156 choty          147 chckhody        144 shod            124 otol            118 cheeaiin        109 qotchaiin      108 chcthod        104 chodalchy      103 shes            102 chcthey        100 chockhy        99 cheeey          99 qokchaiin      90 qokchol        89 okor            85 qokcheey        84 qokeeor        80 chopchol        78 Top 30 chunks used ch        3333 sh        1735 qo        1705 ey        1406 ckh        1056 ody        926 or        920 ok        793 ee        779 ot        726 cho        722 cth        687 ol        604 kch        591 aiin      570 es        562 y          448 ke        414 od        376 al        360 yk        349 os        315 chy        274 tch        259 ees        249 op        249 eey        203 eo        191 ar        186 ty        185 Top 30 character bigrams ch    6311 ho    4805 he    2686 ee    2417 ok    2375 qo    1967 sh    1960 od    1924 ey    1923 hc    1590 ot    1453 or    1345 kc    1329 ck    1324 kh    1324 dy    1142 ai    951 es    928 ol    875 in    866 ct    851 th    851 ha    840 ii    835 ke    759 oc    673 al    603 eo    529 hy    525 da    460 Top 30 character trigrams cho  2659 hod  1602 chc  1590 kch  1329 ckh  1324 hey  1293 qok  1231 che  1214 ody  1142 sho  1113 hee  1095 okc  1061 hor  995 hck  926 cth  851 aii  834 iin  759 ees  753 she  745 oke  719 hct  664 eee  661 kho  626 hol  579 khe  568 kee  566 eey  547 cha  522 qot  428 otc  419 >>>