Experiments with mapping - Printable Version +- The Voynich Ninja (https://www.voynich.ninja) +-- Forum: Voynich Research (https://www.voynich.ninja/forum-27.html) +--- Forum: Analysis of the text (https://www.voynich.ninja/forum-41.html) +--- Thread: Experiments with mapping (/thread-4118.html)

Experiments with mapping - dfs346 - 07-12-2023 When I first started juxtaposing the frequency table of Voynich glyphs with the frequency tables of selected medieval European languages, an experiment naturally suggested itself. This was to take a random page from the Voynich manuscript and map glyphs to letters, one by one from the top of the frequency table to the bottom. This might produce a few recognisable words; or it might not. I did indeed try a few experiments of this nature, starting with the v101 transliteration as the source document and with medieval Italian (as per the OVI corpus) as the destination language. I did the mapping in Microsoft Excel, which has a convenient “find-and-replace” function. Since Excel tends to treat upper and lower case as the same, I first replaced all upper-case keyboard assignments in v101 with similar lower-case Unicode characters: for example, v101-K became ǩ and v101-W became ŵ. I also made the decision to replace all occurrences of v101-4o (which I believe is a single glyph) with the Unicode character ④. Not unexpectedly, these experiments did not yield recognisable words. For example, having randomly selected page f090r1, the first two lines: goeccoe ④hcoe ④ŵ1o8 1oe9 ǩop / 92oe koy 2coy ④k1oy ④h9 8ayaea mapped to: BEROOER CTOER CŵNEL NERA QUEF / APER DES POES CDNES CTA LISIRI. (In this instance, the v101 glyph ŵ could not be mapped at all, since this glyph is relatively rare, and the medieval Italian alphabet had only 33 letters including accented vowels. So I ran out of Italian letters before I ran out of Voynich glyphs.) However, later on when I became aware of the Sukhotin algorithm, it made sense to try a variant of this approach, with vowels distinguished from consonants. With the v101 transliteration, the Sukhotin algorithm (as implemented by Dr Mans Hulden’s Python code) identifies the following v101 glyphs as the most probable vowels (in descending order of probability): o, a, 9, c, ④, C. (There are six vowels here, but we might need to conjecture that C could be a double c.) That enabled me to construct another juxtaposition of frequency tables, as follows:     This in turn permitted another series of experiments with mappings, on which I will report in another post. RE: Experiments with mapping - dfs346 - 08-12-2023 Register or login to view the content