n-grams while ignoring spaces?

[MarcoP]

I tried an experiment on Q13 based on the ideas discussed in this thread. As always, it is well possible that I made errors.

I used the ZL3a-n.txt EVA transliteration where benched, benched gallows and i/e-sequences were replaced by uppercase letters.
In the processing, all spaces are removed. For two consecutive characters X and Y, the ratio between the actual frequency of the XY bigram is compared with the expected frequency as freq(X)*freq(Y) (similar to the method Emma and I used in our paper about word-break combinations). When the ratio drops to less than 50% of the previous value, a “break” in the sequence is inferred (same threshold discussed in the Whale paper by Arnon et al.).

Original EVA and script output for the first 5 lines of You are not allowed to view links. Register or Login to view. (I treated the initial weirdo as p).

pykedy.olfchedy.qokedy.spchy.chedy.rol.dor.ofchedy.qokedy
pykEdy olfC EdyqokEdys pC yCEdy rol d orofC EdyqokEdy

olshedy.qokedy.rshedy.cthdy.otedy.kedy.dal,dal.dol.oty.dal
olSEdyqokEdy rSEdy Tdy otEdy kEdy dal dal d ol ot ydal

qokedy.chety.qolshedy.okedy.dol,eesolchey.qotedy.ol,dam
qokEdy CE tyqolSEdy okEdy d ol EsolCE yqotEdy ol dam

ol,chy.lshdy.lcheckhy.ol.keedy.lcheckhey.l,olkedykain,ol
olC ylS dy lCE Ky ol kEdy lCE KEylol kEdy kaIn ol

qor.olkeey.olkain.ol.chsey.ol.cheeky.dar.okal.dal.olchedy
qo rol kEyol kaIn olC s EyolCE kydar okal dal olCEdy

Large image showing plots for each character transition:

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The results are mixed. In several cases, Voynich spaces tend to follow the criteria discussed here, i.e. they tend to occur between two characters that are not tied by a strong sequential correlation. Results for the second line are particularly good. But many of the inferred spaces do not match the actual text; an obvious problem is yq which is never detected as a break in the sequence, since in Q13 it’s a frequent bigram when spaces are ignored.