The Voynich Manuscript

This is a collection of various computational methods I have used in an attempt to get some understanding of the cipher used in the Voynich manuscript.

Strong's Cipher

Supposing that Strong's conjecture about the structure of the VMs cipher is correct, we use a computational method to try to infer the alphabets and their sequence with the use of a large Latin diictionary.

Details are here.

Mapping the Voynich Manuscript to Music

Using a Java Media Framework MIDI application that processes the Voynich text, aach character is mapped to a note on the MIDI scale in a two octave range: Note = 48 + i mod 24

Each word is played as one or more chords of these notes, using the Grand Piano instrument.

If a gallows character ("h" or "k") appears in the word, then the notes preceding the gallows character are played as a chord, followed shortly by the notes after the gallows character, but shifted by either 1 octave ("h") or two octaves ("k"). If the character "9" appears as the last in the word, then the delay before playing the next word is reduced.

Using this method, here is what the common Voynich word "8am" sounds like: 8am

The word "okoe": okoe

The word "4ohc89": 4ohc89

And the complete Folio f1r (a long pause is taken after each paragraph on the folio): Folio f1r

And Folio f3r

Folio Similarities

More details here.

A Phonetic Attack

Comparing the phonetic content of various texts with VMs "words", using "Soundex" and "Double Metaphone"

For details, go here.

Phrase Analysis

This study is based on the idea that the Voynich "Words" are in fact codes for parts of plaintext words. The Voynich symbol "9" is used to delimit the words. A Genetic Algorithm is used to explore the cipher, using a large body of common Latin phrases (as opposed to single words).

For details, go here.

Vowel/Consonant Group Encryption Scheme

For details, go here.

Transitions between Glyphs

This study looks at the probabilities associated with glyph sequences in the VM. E.g. which is the most likely glyph to find at the beginning of a word in the herbal section?

For details, go here.

Anagram Analysis of Star Labels etc.

This investigation was inspired by Robert Teague's deciphering of e.g. f68r3.

For details, go here.

Analysis of the Prefixes, Stems and Suffixes in the Voynich Manuscript

Extract:

For N=3, looking at the Herbal folios f1v-f20v inclusive, 1331 different words. 

Confirmed valid prefix/stem/suffix counts 99 252 111 
Prefix/Stem/Suffix frequency, normalised 
4ok     0.1010101               o89     0.05952381              o89     0.09009009 
4oh     0.07070707              1oe     0.055555556             8am     0.09009009 
1oe     0.060606062             4ok     0.055555556             1c9     0.054054055 
1oh     0.04040404              8am     0.04761905              1oy     0.054054055 
ok1     0.04040404              4oh     0.04761905              1oe     0.045045044 
8oe     0.030303031             1oy     0.03968254              coe     0.036036037 
1oy     0.030303031             1c9     0.031746034             cc9     0.027027028 
1co     0.030303031             1co     0.023809524             e89     0.027027028 
1ok     0.030303031             8oe     0.023809524             ham     0.027027028 
4oj     0.030303031             coe     0.01984127              2c9     0.027027028 

For more results, go here.

Useful Links

This is by no means an exhaustive list, but these are some of the Voynich sites/pages I have found useful, interesting and/or amusing.

Rene Zandbergen's site

http://www.voynich.nu/

Voynich Central

http://www.voynichcentral.com/

Elmar Vogt's blog

http://voynichthoughts.wordpress.com/

H.R. Santa Coloma's site

http://www.santa-coloma.net/voynich_drebbel/voynich.html

Philip Neal's webpages

http://voynichcentral.com/users/philipneal/

Attempts to crack the cipher with Genetic Algorithms

Some Assumptions about the VM text

My assumption in the work with Genetic Algorithms (GAs) is that the Voynich is a terse, compressed, abbreviated n-Gram conversion of the plaintext language. The scribe would have consulted a table of n-Grams while converting the Latin (or whatever) to the VM text, perhaps even writing the enciphered words out on a separate work sheet before copying them into the VM.

For example, assume the following extract from a set of possible n-Gram conversion rules (or "mappings") used by the scribe:

then, to convert the English word "hypothesis" to Voynichese, we do as follows:

h => f

y => a

pot => oc

he => c

s => 8

is => 9

so that "hypothesis" => "faocc89"

The inverse mapping can be used to decode the Voynich word (perhaps not unambiguously ...).

Clearly, there are a very large number of possible n-Gram mappings!

Candidate Decipherings of f27v

Go here to look at folio 27v, and see the various Genetic Algorithm attempts at deciphering the text.

Voynich Herbs

Edith Sherwood has a web site where she details compelling possible identifications for the plants depicted in the "herbal" pages of the VM.

Dana Scott's page also has plausible identifications for the plants.

As has often been pointed out, if we look at the first Voynich "word" that appears on each page of the herbal part of the VM, we find that those words are unique, or appear elsewhere very rarely. It thus seems reasonable that the words may be the names of the plants depicted.

The GA was set up to find a set of n-Gram mappings that would convert a list of 111 Voynich first herbal words into Latin/English or Spanish. For this, dictionaries of Latin, English and Spanish herb/plant names were used.

The GA sought a mapping that would convert all the Voynich words for herbs/plants into as many valid plaintext (Spanish, English, Latin) words as possible. The best result was for a mixed English/Latin dictionary (see table): 31 of the 111 Voynich words were converted, about 30% success rate.

(One should never expect 100% success, due to missing names in the dictionary, transcription errors, missing n-Grams, incomplete n-Grams etc..)

The results are shown below in tabular form, together with Dana Scott's and Edith Sherwood's identification. The first column shows the folio in the VM, the second shows the first Voynich word on that folio. For the GA identification columns (3 and 4) the Voynich mapped word is shown, in quotation marks if not found in the associated dictionary, and in bold if found in the dictionary.

Note that, probably unsurprisingly, nowhere do the IDs from the GA in Spanish, English/Latin and Scott/Sherwood, agree! NOT YET, anyway :-)

(What amuses me about about this mapping technique is that it tends to produce words that sound plausible in the target language. E.g. for f4r the Latin/English word "paptise" sounds like a valid word.)

Character Analysis

See the section "Bibliography" at the end for the provenance of the various texts used.

• Voynich. The Herbal folios from the Voynich are processed, generating frequency tables for single characters, dual characters (digraphs), trigraphs and quadgraphs (1/2/3/4). These are also called n-Grams. Frequency tables for word lengths and common words are also generated.
• Latin. A few books from Augustinus and other places (see Bibliography)
• A German cookbook from 1553
• The Book of the Courtier, in English from 1561
• French from 1367
• a Latin Herb garden description
• Spanish from C16

Here is the ranking of the most popular words in each text (full tables are available in the Excel spreadsheet)

The 1/2/3/4 n-Grams are calculated as follows. Suppose the word "sesame" appears in the text. The following counts are made:

• "s" 2
• "e" 2
• "a" 1
• "m" 1
• "se" 1
• "es" 1
• "sa" 1
• "am" 1
• "me" 1
• "ses" 1
• "esa" 1
• "sam" 1
• "ame" 1
• "sesa" 1
• "esam" 1
• "same" 1

Then, each count is weighted by the length of the group, yielding s=2, e=2, a=1, m=1, se=2, es=2, sa=2, am=2, me=2, ses=3, etc. The counts are added to running sums for each distinct group found, and normalised at the end of processing.