To what extent should the translation respect the grammar?

[MichelleL11]

The closest I can think of would be some kind of comparison of the frequencies of the most frequent words. As discussed You are not allowed to view links. Register or Login to view., languages have a closed set of function words typically including at least half of the 10 most frequent words in any reasonably long text. A few years ago, You are not allowed to view links. Register or Login to view. that checking how the most frequent Voynichese words are interpreted by a proposed solution is an effective way to evaluate a theory: in my opinion, this test is the simplest possible way to see if a solution has any hope of making sense grammatically. 

Hi, Marco:

Thank you for bringing up the next level of issues with Voynichese (e.g. a level up from conditional entropy) -- the word pattern statistics.  I definitely agree that word pattern is more closely related to the "grammar" topic of this string than any other measured statistic.

I know you are very well aware of this but some aspects of word patterning does look like a natural language (e.g. the text "obeys" Zipf's law, arguably only "approximately" (You are not allowed to view links. Register or Login to view.) or perhaps more tellingly, the Voynichese word lengths' adhere to a gamma distribution (You are not allowed to view links. Register or Login to view.), and "Key words and Co-occurrence" looks like natural language (You are not allowed to view links. Register or Login to view.)).  But all is not rosy in word pattern land: there are too few word pattern repeats compared to what is found in most natural languages (You are not allowed to view links. Register or Login to view. and You are not allowed to view links. Register or Login to view.) -- which is precisely what you would be looking for in order to infer some sort of grammar.  Because what is grammar but (on a high level) other than repeating patterns of words in order to communicate?

This situation (coupled with all the myriad of ways functional words can present in a language) has made it impossible to identify so-called "functional" words in the Voynich -- which has been discussed You are not allowed to view links. Register or Login to view. and in your parts of speech experiments (You are not allowed to view links. Register or Login to view.).  But these functional words (particularly "short indication words") are those that are found at the highest frequency in many natural languages.  Of course, this is complicated by the many ways that natural language can represent functional words (e.g. as separate words, as prefixes, as suffixes, etc.). But intense attempts to link even one Voynichese word (or even perhaps, some word portion) with some sort of function have been unsuccessful to date.

All this verbiage is to say that I am extremely concerned that the highest frequency words in the underlying plaintext are not consistently encoded in Voynichese (or said another way -- the highest frequency words in Voynichese (at least -- maybe, all?) represent different plaintext words.  Or the words maybe are consistently encoded but have been re-ordered in some manner that results in the strange reduplication coupled with lack of longer word repeats.  And we would need some sort of consistent pattern for how either or both (gasp! please not) encoding methods work in order to make any headway.

Maybe this is just catastrophizing - but this is one of my biggest concerns with this work and I do not know how to address whether or not this is the case with statistics.  Maybe there is some thought on experiments that could be done to try to tease this out?  Does the MATTR experiments (You are not allowed to view links. Register or Login to view., You are not allowed to view links. Register or Login to view., and You are not allowed to view links. Register or Login to view., which I just realized I haven't yet discussed and do belong in this general category of word patterns) help distinguish these possibilities in any way?  I will definitely be thinking about it . . .