An attempt at extracting grammar from vord order statistics.

[davidd]

Hi,
I find the text file somehow hard to read, so I haven’t analyzed it in detail.

I tried something similar a few years ago. I wrote two posts based on Part Of Speech POS-tagging software. I only considered Quire20 and (in the update post) Quire 13. I only experimented with a small number of word-classes (from 5 to 8, IIRC).
The process gives decent results for the English King James Genesis: but that’s a very repetitive text with particularly low MATTR. Voynichese is much tougher, so it’s not clear that we have enough coherent text to process.

You are not allowed to view links. Register or Login to view. (2019)

Here I found that groups of words for Voynichese include types that are more similar to each other than for English: if two words are similar, they behave similarly (while in English this is not necessarily the case: better/butter which/witch bare/bear etc).

I also found that Voynichese grammar tends to have loops, where words belonging to the same category follow each other (a trivial case is the consecutive repetition of identical tokens). I am not sure about how such loops are handled in your experiment. Have you noticed that there are word-classes that tend to appear with consecutive tokens? This is of course something that doesn't happen frequently in English.


You are not allowed to view links. Register or Login to view. (2021)

If one considers the newline separator as a symbol, the inferred grammar is based on LAAFU: there’s a class for line-initial words and a class for line-final words (e.g. ending -m).

I then applied some simple transformations (partly based on You are not allowed to view links. Register or Login to view.) to remove line effects (e.g. word initial s-, which typically is line-initial, was removed, assuming that saiin is a line-initial variant of aiin).
At this point, I removed the newline symbol from the input data and analyzed whole paragraphs instead.
The positive result I found is that Q20 and Q13 produce grammars that are somehow comparable. I created graphs where word-classes that often follow each-other are connected by arrows (npnp is the paragraph-separator).


It seems that there is some overlap with your results e.g. 

• the bidirectional arrow between shedy/chedy and qokain/qokaiin
  
• the Q13 sequence qokain->dar->ol
  

Not yet implemented the EMS

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I will have a look at producting dot files from my statistics, better legible than raw text files

the format of the text file is largely based on what is pleasant for me to watch in the terminal. also my arbitrary choice of having 18 groups is chosen on that point,