Interesting result for f3r with an ngram Genetic Algorithm

[MarcoP]

I am looking for a way to reward small improvements for the GA to chew on without selecting too much fake Latin. The idea is not to make a lorem ipsum generator. So I was thinking about something like this:
- count actual Latin words as correct with score = word length
- count common Latin bigrams and trigrams (a selection of 20-50 for example) as correct with score = a small percentage of their total length

The statistics of Voynichese make clear that it cannot be a simple substitution code for Latin. Independently from the specific language, I think it could be a good idea to consider frequency as well:
autem and super should have higher scores than seror and loris.

I think the statistics will look very different for an n-gram substitution scheme with nulls, as opposed to a simple substitution scheme which is clearly discounted.

Hi Julian,
if I understand correctly, you are assuming that space are relevant: each Voynichese words corresponds to a single Latin word. I think there is plenty of evidence suggesting that spaces are relevant, so this assumption seems reasonable to me. 

Have you seen this page by Rene?
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I reproduce one of his graphs (ignore the digraph curves at the bottom).
red 24 pages of herbal-A, in Curva
blue 24 pages of herbal-B, in Curva
green Genesis (Vulgate)
grey De Bello Gallico (Latin)

The four lines illustrate different word "types" as a function of the length of a text sample.
The gray line (Cesar) tells us that 2000 words of this text typically include about 1100 different words. The figures for Voynichese are close (about 1000 different words). The other Latin sample (the Vulgate) provides about 750 different words.

Since the figures are comparable, as Rene writes, a Latin to Voynich (or Voynich to Latin) conversion should "maintain the length of the vocabulary". The introduction of nulls can only reduce the vocabulary (e.g. if EVA:t is a null, choty and choy will become a single word). If one considers the Vulgate as a bottom bound, there is some margin for the introduction of nulls, but not much.

Also, Latin words tend to be averagely longer than EVA words. Word length is harder to match if one introduces nulls.