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Abstract
The International Conference on the Voynich Manuscript 2022 at the University of Malta has covered many aspects of the current Voynich manuscript research. We discuss a representative selection of the conference proceedings, in particular the question of existing versus non-existing linguistic structures that indicate some underlying meaningful text.
Notes
1 Obviously, in that case the encryption scheme would have to preserve the linguistic structures.
2 Sometimes this is also called cosine similarity or cosine distance.
3 A similar plot has been presented by Zandbergen (Citation2003b), defining the correlation between two pages as the number of tokens common to both pages.
4 See Timm and Schinner (Citation2020): “No obvious rule can be deduced which words form the top-frequency tokens at a specific location, since a token dominating one page might be rare or missing on the next one.”
5 Another source for the bias could be afterthought glyph modifications in just finished pages. Note that you can easily change <ch> to <sh>, and <k> to <t>, but not vice versa. For a meaningless text such replacements merely would adjust its optical appearance.
6 It can be done by a simple adjustment of the list of preferred prefixes.
7 To avoid discussions about the possibility of different encoding tables corresponding to different sections (Currier languages) we have restricted the calculation to the statistically homogeneous “Recipes” section.
8 As suggested by Table 2 in Hermes (Citation2022).
9 Unless the table has as many columns as there are letters to encrypt. In that case the procedure turns into a one-time pad cipher, for which (provided perfect randomness of the key) the impossibility of breaking it can be mathematically shown.
10 In Bowern and Lindemann (Citation2021), the authors write: “Our work argues that the character-level metrics show Voynichese to be unusual, while the word- and line-level metrics show it to be regular natural language and within the range of a number of plausible languages.” However, here they explicitly mention “unusual word-level predictability.”
11 “No obvious rule can be deduced which words form the top-frequency tokens at a specific location, since a token dominating one page might be rare or missing on the next one” (Timm and Schinner Citation2020, p. 3).
12 Actually the paper does not refer to any word of the VMS text. It only lists some Z-score metrics and states that the “individual metrics vary substantially.”
13 Volunteers were recruited to write short “gibberish” documents, as a basis for a statistical comparison with the VMS and linguistically meaningful texts.
14 This refers to the “self-citation” algorithm (Timm and Schinner Citation2020).
Additional information
Notes on contributors
Torsten Timm
Torsten Timm, diploma in computer science at the Friedrich-Alexander University of Erlangen-Nürnberg, works as a computer scientist in Dresden, Germany. In 2005 he published a book about his research on the Phaistos Disk. His previous research on the Voynich Manuscript focused on a detailed analysis of co-occurrence patterns for similar tokens. In 2014 he published a new generation method for the text in the Voynich Manuscript.
Andreas Schinner
Dr. Andreas Schinner is a theoretical physicist, performing freelance research at the Johannes Kepler University in Linz, Austria. His main area of scientific interest is theoretical solid state physics—particularly particle beam interactions with matter. He is also working as a self-employed software developer.