The Voynich Project · a reproducible open-science investigation
Inside the Voynich manuscript: what the numbers actually say
This project is the work of one curious independent researcher: not a professional cryptographer, linguist or medievalist, just someone who wanted the truth more than a theory. Amateur status is not an excuse for amateur standards. It is the reason the standards here are strict. Every claim is a falsifiable test with an explicit null model, pass/fail rules are written down before results are seen, failures are published with the same prominence as successes, and everything on this page can be rerun, in your browser or from the free code below.
The Voynich manuscript is a real 600-year-old book in an alphabet nobody can read.
It is not random scribbling, the text has deep, reproducible structure.
It is not a simple cipher of any known language, the letter statistics make that mathematically impossible.
It has a real grammar that survives every test we could throw at it, even deleting all the spaces.
But a deliberately meaningless process can fake that grammar, so structure alone doesn't prove meaning.
Across all distances, the text shows no flow of ideas from line to line, so it is not ordinary prose.
Two explanations survive: an elaborate meaning-free formal system, or a list-like reference book in a lost notation whose key no longer exists in the manuscript.
Every "translation" you have read about fails the measurable checks on this page, and you can rerun all of them yourself, free.
Jargon-buster: the words this page keeps using
Every term below also has a dotted underline the first time it appears in a section, hover or tap it for a one-line reminder.
Entropy (predictability)If I say "the cat sat on the ___", you can guess "mat", that's low entropy (predictable). If I say a random word, that's high entropy. Voynichese letters are unusually easy to guess from the letter before them.
Zipf's lawIn any real language, a few words (like "the", "a") are used constantly, and most words are rare, and the drop-off follows a precise curve. Voynichese words follow that exact curve, like a real vocabulary.
Null model / controlThe "boring explanation" we test against. Before asking "is this surprising?", we ask "what would this number look like if nothing interesting were going on?", e.g. shuffled letters, or a fake Voynich text written by a simple machine.
Grammar / morphologyThe rules for how word-parts combine, e.g. in English, "-s" usually means "more than one", and it changes what kind of word can come next. We tested whether Voynichese endings behave the same way.
z-scoreA way of saying "how surprising is this, in standard units of luck". z=2 is "somewhat surprising"; z=6 is "essentially impossible by chance". Bigger = stronger evidence.
Currier A / BIn the 1970s, codebreaker Prescott Currier noticed the manuscript's handwriting and word-statistics split into two distinct "dialects", nicknamed A and B. Both appear in the same book, sometimes on facing pages.
r (correlation)A number from -1 to 1 measuring how strongly two things move together. r=0 means no relationship; r≈0.55 (this page's grammar result) is a moderately strong, consistent relationship, about as strong as everyday cause-and-effect patterns get in messy real-world data.
The story: no jargon, promise
How a curious amateur ended up interrogating a 600-year-old book
Act I · The book that says nothing
A mystery with a century of famous failures
In 1912 a rare-book dealer named Wilfrid Voynich bought a small, strange book. Every page is full of confident, flowing handwriting, in an alphabet that exists nowhere else on Earth. Drawings of plants that don't exist. Naked figures bathing in green pools connected by pipes. Star charts for no known sky. The men who broke Germany's codes in both World Wars tried to read it. Professors, computer scientists, AI labs. Everyone failed. Most people who tackle this book start by guessing what it says.
I started somewhere humbler: what would I have to measure to catch it lying?
Act II · The interrogation
You can't read it: but you can make it answer yes/no questions
Here's the trick that makes this whole project work. You don't need to understand a text to ask it questions like: Do your words repeat the way a real language repeats? Is your "alphabet" used the way alphabets are used, or the way numbers are used? If I cover the spaces, do your words still know where they end? Each question has a measurable answer, and, this is the important part, a way to know what the answer would look like if the book were lying. For every test, we also ran it on Latin, English, Finnish, Turkish, on shuffled decoys, and on fake Voynich text written by a machine we built for exactly this purpose. If the real book and the decoy give the same answer, the test proves nothing, and we say so.
Act III · The twist
It has grammar. And that means less than you'd hope.
The book passed tests no gibberish should pass. Its words obey rules about what kind of word comes next, grammar, and that grammar survived everything we threw at it, including deleting every single space and letting an algorithm re-cut the text blind. For a week it felt like standing at a door about to open.
Then we did the thing you're supposed to do to your own best result: we tried to kill it. We built a mindless machine, a mechanical scribe with three copying habits and no idea what it was writing, and its output passed the grammar test too. The door slammed. Structure, it turns out, is cheap. Meaning is not. Knowing the difference is the whole game.
Act IV · The funerals
We buried fourteen of our own theories. In public.
Maybe the line-end words are sums, like a ledger? Tested. Dead. Maybe the zodiac labels are day-numbers? Dead. Maybe the star cluster that looks like the Pleiades is labeled "Pleiades", a crack to pry open, like the names that cracked Egyptian hieroglyphs? Dead, chance look-alikes. Maybe it's Turkish-like, as one famous theory says? We built a dictionary of 700-year-old steppe-Turkic from a medieval phrasebook to test it properly. Dead. Maybe a famous hoax-machine design from 2004 explains it? Dead, it can't even produce enough different words.
And the one that explains why you've seen so many confident "translations" in the news: we let a computer search for the best possible way to assign sounds to Voynich symbols so that words decode into real Latin, Greek, or Turkic words. It happily "translated" more than half the book. Then we ran the same search against fake dictionaries of scrambled non-words, and it did just as well. That number is the size of the illusion every published translation fell into. The book lets you see whatever you bring to it. That's why our rule is: the data gets a vote, and the data's vote is final.
Act V · Where the trail stands
Two suspects left: and an honest map for whoever comes next
After sixty-plus experiments, two explanations are still standing. One: the book means nothing, an elaborate formal performance, written by hand-habits that drifted slowly across the months of work (we can actually watch the drift, page by page; it even tells us the original page order). Two: the book is something like a reference manual, lists, recipes, properties, one entry per line, in a notation whose key was never in the book at all. The text alone cannot pick between them. Anyone who says otherwise, ask them to pass the lab at the bottom of this page.
What we leave behind is not a translation. It's something we think matters more: the first complete, reproducible map of what this book is and is not, every road in, every road that dead-ends, every tool free, so the next curious person starts where we stopped instead of where we started.
Why trust an amateur's map? Because you don't have to trust it. Every claim above is a number, every number comes from code you can run, and the experiments that failed are documented as carefully as the ones that worked. That's the difference between a story and a scientific story.
The object
A 600-year-old book nobody can read
Beinecke MS 408, the Voynich manuscript, at Yale, is a ~240-page parchment book, radiocarbon-dated to the early 1400s, filled with botanical, astronomical and bathing illustrations and roughly 38,000 words of flowing script in an alphabet that appears nowhere else on Earth. It has resisted every professional and amateur decipherment attempt for over a century, including the WWII codebreakers who cracked Enigma-era ciphers.
f68r: astronomical diagram with the labelled-star register (Beinecke MS 408, Yale; public domain)f72r2: zodiac medallion; the ring text behind the day-number hypothesis we falsified (Part 52)f68r3 detail: the Pleiades and the hapax label doaro: our best image crib, honestly inconclusive (Part 51)
Worked example, the words this page uses for "where something is"
illustration (plant, star, bathing figure…)
qokeedy shol daiin chedy qokain
otaiin qokedy chey shol daiin ol
qokeedy dal qokedy qokedy chedy
cheol daiin shol qokain otaiin
Folio / page, one side of a sheet of parchment; the manuscript has ~240 of them (numbered like 68r, 72r2 in the captions). Paragraph, a block of lines, usually starting with a tall "gallows" glyph. Line, one row of writing; our "records" finding (below) is about what happens within vs across these. Word / token, a glyph-cluster separated by spaces, like qokeedy. Glyph, a single written symbol, the Voynich equivalent of a letter, but, as the entropy section shows, glyphs don't behave quite like letters in any known alphabet.
Instead of proposing another reading, this project did something more boring and more useful: it measured the text, exhaustively, with controls, and let the numbers eliminate explanations until only one family survived.
Findings 1 & 2
It's not random: and it's not a simple cipher of any language
In plain words: every language has a measurable "predictability fingerprint". Voynichese is far more predictable than any of the 13 languages we tested, too predictable for a simple letter-swap cipher to produce. Whatever this is, it is not Latin (or anything else) with funny letters.
Voynich word frequencies follow Zipf's law exactly like a real language (a random-scribble control fails badly). But the predictability of each next letter, conditional entropy, is far below every natural language. A substitution cipher cannot lower this number: you cannot get 2.0 bits from enciphering 3.3-bit Latin letter-by-letter. Every "I translated it into Latin / Hebrew / proto-Romance" headline collides with this single chart.
Worked example, what "predictable" means here
In English, after the letter t you might see h, o, r, a, i, e, lots of options ("the", "to", "tree", "tap"...). In Voynichese, after the glyph q the next glyph is o essentially every single time, there's almost no choice. Multiply that effect across the whole alphabet and you get a number, 2.09 bits, that says "this text has roughly 4x fewer real choices per letter than English". A simple letter-swap cipher can only relabel the letters; it can't remove choices that were there in the original language. So whatever produced this text, it wasn't "take a normal language and swap the letters".
Conditional letter entropy (bits per character), computed identically for all corpora. Lower = more predictable. Voynich: 2.09. No natural language tested comes near it; no letter-substitution cipher can produce it from one. Want to measure your own text on this axis? The Theory Lab below runs this exact battery in your browser.
Stranger still: where a word sits on the page changes how it is spelled. Words ending in the glyph m are 17× more common at line-ends; words containing p or f are 17× more common in paragraph-opening lines; 82% of paragraphs open with a tall "gallows" glyph. No natural language does this, open any folio in the explorer below and you can see it yourself.
Finding 3 · interactive
A medieval scribe could write this: try it yourself
In plain words: we built a mechanical recipe, three copying habits and a word table, that writes text statistically almost indistinguishable from the manuscript. A 15th-century scribe could have done this with no meaning at all. That doesn't prove they did; it proves the surface statistics can't tell you.
We built an 11-parameter mechanical recipe, a word-table plus three habits (reuse a word, mutate a recent word, compose a new one) plus the layout rules, and tuned it against the manuscript. It reproduces nearly the entire statistical fingerprint, including the letter entropy to the third decimal. The studio below runs that exact fitted model in your browser, and hands you the dials: drag a habit off its fitted value and watch the live fingerprint meters drift away from the manuscript's targets.
ReuseCopy a word you (or a previous scribe) already wrote earlier on the page
→
MutateTake a recent word and swap one piece, like writing "qokedy" then "qokeedy"
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ComposeBuild a brand-new word from the same prefix/middle/suffix pieces as everything else
Think of it like a scribe with a personal "phrasebook" of word-pieces, who mostly recycles and lightly remixes recent words, and occasionally snaps together a new combination from the same Lego set of pieces, with no idea what any of it means.
Loading the generator studio…
Free tool · the honest "translator"
There is no translator: here is the next best thing
Nobody can translate Voynichese. Not us, not anyone, every published "translation" fails the falsification lab below, and saying so plainly is part of doing this honestly. What 60+ experiments can give you is everything measurable about any word: its slot anatomy, how often each "language" uses it, which sections it lives in, its near-twin neighbours, and now every place it occurs in the manuscript, in context. Type any EVA word (or click a suggestion):
Worked example, anatomy of a word
qokeedy
Almost every Voynich word splits cleanly into three slots, like a tiny assembly line: a small set of opening pieces (prefix, here qo), a short core (middle, here k), and a small set of closing pieces (suffix, here eedy). It's a bit like English words built from prefixes and suffixes (un-believ-able), except in Voynichese, nearly every word is built this way, from a surprisingly small shared parts-bin.
Loading the word analyzer…
Findings 4 & 5
It has rule-governed sequence: but that isn't proof of meaning
In plain words: Voynich words obey rules about what kind of word comes next, like grammar. We confirmed it in three independent transcriptions, and it even survives deleting all the spaces. But we also showed a meaningless machine can produce grammar this strong, so we refuse to call it proof of meaning. That refusal is the most important sentence on this page.
Voynich words come in suffix-swapped pairs across dozens of unrelated families (qokedy / qokeedy, chedy / chey). We measured whether the suffix changes a word's following context the same way in every family, and it does, at the strength of real English morphology (and it replicates in a second, independent transliteration, across separate physical quires, and even in the other Currier dialect on its own markers). A context-free "scribble" generator scores zero on this, so the text is genuinely not context-free pseudo-text.
Worked example, why a "suffix" can prove grammar
In English, "-s" mostly means "plural", and that has a knock-on effect: after a plural noun like dogs, you're more likely to see a verb like run than after the singular dog (which prefers runs). The suffix changes what's allowed next. We tested whether Voynichese suffixes do the same thing: does qokedy vs qokeedy change what kind of word tends to follow, and is that change consistent across dozens of unrelated word-families that share the same suffix pair? The answer is yes, about as consistently as real English "-s" does. That's the signature of grammar. But, and this is the twist, a machine with no idea what it's writing can produce that same signature, just by picking the next word's "category" from the previous word's category. So this test proves rule-following, not meaning.
Split-half context consistency. The honest scorecard, after a steelman test: the Voynich matches real English morphology, but a meaningless class-conditioned Markov process (which just picks the next word from the previous word's class) also reproduces it (0.51), while a context-free generator cannot (0.00). So this proves rule-governed class-sequential structure, not semantic content, we narrowed our own headline claim when the steelman passed. Replay this experiment with its controls in the notebooks below.
Clustering the 236 most frequent words purely by context, the algorithm never saw a single letter, yields eight coherent word classes with stable transition rules (an -or/-ar word is followed by a particle 53% of the time; dedicated line-opener and line-closer classes emerge on their own). The structure is real and deep; whether it carries recoverable meaning is a separate question the text alone cannot answer, see the audit and the model below.
Findings 6 & 7
The page is a topic. The line is a record.
In plain words: words repeat heavily inside a line and stop repeating at the line break, like rows in a ledger, not sentences in a paragraph. If this book says anything, it says it one line at a time.
Two discoveries about structure. First: vocabulary locks onto the illustrated subject, even within a single scribe's handwriting, plant-pages and bathing-pages use measurably different words (ruling out "different scribes' habits"). Second: the famous repeated words (qokedy qokedy dal qokedy qokedy) turn out to respect line boundaries perfectly:
Probability (per 1000) that a word recurs at distance d, within its own line vs across a line break, at matched distance. Voynich recurrence drops off a cliff exactly at the line break; our distance-based generator (dashed) can't see lines at all. A scribe's memory doesn't reset at line ends, but a record does.
Worked example, what "the line is a record" looks like
Compare two ways of writing about three plants. Prose carries an idea across line breaks, you need the previous line to understand the next. A ledger restarts each line as its own self-contained entry, often repeating a key word:
Prose (ideas flow across lines)
The root of this plant, when dried and ground to powder, eases the stomach if taken with warm wine before the evening meal each day.
The burst-chart above shows Voynich text behaves like the right-hand column: a word that just appeared is much more likely to reappear within the same line than after a line break, exactly the fingerprint of restated, record-like entries, not flowing sentences.
Together: each page treats a topic; each line behaves like a self-contained record that restates its subject, the texture of inventories, recipes and tallies, not of sentences and stories.
Finding 8
If a language is underneath: which kind?
In plain words: if there's a language under the encoding, its word-statistics look most like the heavy-suffix family (Finnish, Greek, Hungarian), and least like English. But our vowel-harmony test later cut Finnish, Hungarian and Turkic from the simple-encoding list, so this clue now points at the encoding, not a specific language.
A word-for-word code hides what each word means but cannot hide how the word-stream behaves. So the century's proposed plaintext languages can finally be screened without reading anything. Thirteen languages, identical pipeline, matched corpus sizes:
Worked example, "fingerprint", not meaning
Think of this like recognizing someone's typing style without reading what they wrote: do they use lots of short connector-words, or long words with many endings stuck together? Do words repeat in clusters or spread out evenly? Every language has a "shape" like this, independent of its alphabet or vocabulary. Replacing every word with a code symbol (a word-level code) keeps that shape intact, even though no word is readable any more. So this chart isn't reading the Voynich, it's comparing its "typing style" to thirteen real languages' typing styles. Closest bars = most similar shape (Finnish, Greek, Hungarian, all famous for long words built from many stuck-together endings). Farthest = English, which relies on short separate words and word order instead.
Distance from the Voynich word-stream fingerprint (shorter bar = better match). The top tier is uniformly inflection-rich; the languages most often "deciphered" in headlines: English, Spanish, Hebrew, Arabic, fit worst. The strangest Voynich habit, word-class chaining, exists in only three tested languages: Finnish (1.36), Hebrew (1.20) and Turkish (1.00) vs Voynich's 1.34.
The same ruler, applied to the Indus script
The toolkit generalizes. We built a calibrated "notation ↔ language" scale, validated on Roman numerals (rigid sign-order), decimal digits (no order) and four languages, and placed two famous undeciphered scripts on it:
The Indus script, center of a 20-year "is it writing at all?" dispute, measures more language-like than the Voynich, with a real syntax of dedicated opening, connecting and closing signs. The Voynich sits on the notation side: its words are built like ordered symbols, not pronounceable words. (Preliminary: 178-inscription sample.)
New · the manuscript, open on your desk
Explore every folio of the manuscript
In plain words: this is the entire transliterated manuscript, all 227 folios, every line, every word, with each page's measurable profile next to it. Click any word to send it to the analyzer; watch the slow drift of the scribes' habits move across the book like weather.
Each folio card shows its codicological metadata (quire, scribal hand, Currier dialect, illustrated section), its full running text, and where it sits on the production drift curve: the page-by-page change in writing habits (Part 26) that is the manuscript's only long-range signal, strong enough that it can flag misbound pages. High-resolution scans of every folio are free at the Yale Beinecke library; each card links straight to them.
Loading 33,122 words of manuscript…
New · run the experiments yourself
The experiment notebooks: evidence you can poke
In plain words: the four decisive experiments of the investigation, rebuilt as live panels. Each one lets you flip the control switch, the shuffled text, the meaningless machine, the real Turkish, and watch what honest evidence looks like when the control answers back.
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The surviving model
What the Voynich manuscript most likely is
In plain words: after 60+ experiments, two candidates are left standing: a very elaborate meaning-free system written by drifting habit, or a list-like reference book in a lost notation. The text alone cannot pick between them, and we'd rather say that than pretend.
An encoded compendium of short records, page = topic, line = record that restates its subject, written in a word-level code (each plaintext word replaced by a code token from an alphabetized, domain-organized, partly homophonic key) over a plaintext whose word-stream type is inflection-rich, with the key a separate physical document, now lost or waiting in an archive.
Why this and nothing simpler: hoax/gibberish died on the grammar and topic results; plain language in an exotic alphabet died on the entropy and layout results; letter-cipher died on the entropy math; sequential catalog numbers died on the label tests. The word-level code over an inflected language is the one description that survives all sixteen experiments, including the ones designed to kill it. And one mundane detail explains the manuscript's weirdest feature: if the key was an alphabetized list numbered in order, related plaintext words (think aqua, aquae, aquam) get adjacent code values, which is exactly why thousands of Voynich words differ by a single glyph.
Worked example, how a "word-level code" could create near-twin words
Imagine a code-book where every word of a language is listed alphabetically and given a number, like a dictionary index:
101aqua (water)
102aquae (of water)
103aquam (water, object)
Because aqua / aquae / aquam sit next to each other alphabetically, their code numbers are also next to each other. If those numbers are then re-written in a made-up notation (Voynichese), related words end up looking almost identical, differing by one symbol, the way qokedy and qokeedy do. This single mundane mechanism, an alphabetized index, would explain why ~87% of Voynich words have a near-twin elsewhere in the text, without needing any of it to be readable today.
What this is not. Not a translation, nobody can read the book, including us. Not peer-reviewed, it is a documented, reproducible analysis awaiting hostile scrutiny, which is how knowledge gets made. Several individual findings reproduce prior scholarship (credited in the report); the controls, calibrations, the grammar result and the record-structure results are, to our knowledge, new.
Update (second audit round, Parts 53–63): the picture above survived a second adversarial pass and got sharper. No vowel harmony at sign or unit level (with detectors validated on Turkish and Finnish); no discourse-scale information, the only long-range structure is slowly drifting page register; the grammar survives with the scribal spaces deleted; Rugg's grille and per-letter verbose encodings of abbreviated Latin are both excluded constructively. Whatever Voynichese is, its redundancy is manufactured at the slot/word-assembly level, and if it carries meaning, that meaning lives in line-records, not prose.
Adversarial validation
We invited a hostile review: then ran its audit
An independent reviewer examined the full report and prescribed six "break-it" experiments. We ran all six, each built on a single canonical parser (canonical.py) so every number prints from one auditable pipeline. The verdicts, including the casualties:
How to read this table: each row is a "find the flaw" attempt by an outside critic. Ablation means deliberately removing some of the data to see if the result survives without it. A shuffle trap scrambles the text on purpose, if a test still finds a "pattern" in scrambled gibberish, that test is broken. Green = our claim survived the attack. Red = the attack found a real problem and we retracted or narrowed the claim.
Claim under attack
Hostile test
Verdict
The grammar is an artifact of the EVA transcription
Re-run on the independent v101 transliteration (different alphabet), plus a shuffle trap that catches false positives
Grammar survives (r 0.66–0.81; collapses correctly under shuffle)
The grammar is a one-scribe / one-batch convention
Train on one set of physical quires, test on disjoint quires
-edy/-ey generalizes at the ceiling (r 0.553 vs 0.547); -dy/-y weakens, claim narrowed
The grammar is a layout artifact
Delete line-final, paragraph-initial, and p/f/m words; keep only line-medial words
Survives every ablation (z 4.1–5.8)
The e/i "operator" is just graphic line-fill
Layout covariates vs within-item variance partition
Layout explains <0.5%; the operator is a page-subject-bound graded attribute (refined: not locally contextual)
Lines are rows of a flattened table
Vertical position–class information vs the proper global-edge null
Falsified, the "column" signal was the universal line-edge gradient
Plant names exist as multi-token formulas
Bigram/trigram page-concentration vs a burstiness-preserving null
"No names" holds, the apparent signal was topic burstiness
Methodological lesson worth stealing: two of the six tests initially produced impressive false positives (z = 6.6!) that only the correct null model, within-line shuffles and burstiness-preserving permutations, exposed. Naive permutation tests are not enough for this manuscript.
The scientific method, kept honest
Everything we tried: what held, what died
In plain words: science is mostly funerals. This wall is ours, including five of our own favourite ideas, tested and buried by our own rules.
This is the part most write-ups hide. Each card was a real hypothesis we held long enough to test; each verdict came from a pre-registered pass/fail rule and a null model, not from taste. Killed cards stay published, they are how the surviving picture earned its place. (Part numbers refer to the full lab notebook, REPORT.md.)
Loading the ledger…
Two readings remain standing after all of this: a meaning-thin formal system with drifting production habits (now positively evidenced at long range), or a meaningful line-record formulary under a slot-level encoding whose key is outside the manuscript. The text alone cannot split them further, we say so, rather than pick a winner.
What we measured against
The datasets: all public, all fetchable by script
In plain words: every test on this page compares the Voynich text to something else, other languages, scrambled versions of itself, or machine-written fakes. This table is the full list of "something else". Without these comparisons, a number like "2.09 bits" means nothing; with them, you can see exactly how unusual it is.
Quick definitions: a transliteration (ZL 3b, v101, Takahashi) is a letter-by-letter transcription of the manuscript's glyphs into typeable text, three independent ones exist, made by different scholars, which is how we check a result isn't just an artifact of one person's reading choices. CLTK, bible-corpus and Quran-JSON are public, downloadable collections of real-language text used as "known normal" comparisons. The Digby recipe book and Codex Cumanicus are real historical documents we use as period-appropriate stand-ins for "what writing from this era looks like".
Null machines, what a meaningless process can and cannot fake
generators.py, rugg_test.py
Parsing decisions are documented and sensitivity-tested: the two silent choices in the transcription pipeline (alternate readings, uncertain spaces) move no headline number beyond noise (P55). A fresh clone on a clean machine reproduces every number exactly (P53).
New · the falsification lab
Test your theory against the manuscript
In plain words: anyone claiming a Voynich decipherment now has a bar to clear: produce sample text with your proposed method, paste it below, and the lab measures it against the manuscript's fingerprint, the same battery we publish in the falsification checklist. Every published claim to date fails multiple rows. Yours might not. That would be news.
Paste at least a few hundred words of any text: your proposed plaintext encoded by your proposed method, a "translation" read back into its claimed source language, another language entirely, or your own hand-rolled gibberish. The lab computes the full surface battery, conditional letter entropy, Zipf slope, word lengths, vocabulary concentration, the near-twin network, in your browser (nothing is uploaded), and grades each measurement against the Currier B targets and tolerances.
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What do these rows actually mean? (plain-language glossary)
Conditional letter entropy, how easy each next letter is to guess (see the Jargon-buster above). Zipf slope, how steeply word-frequency drops off from "the most common word" to "the rarest" (real languages have a characteristic slope). Word length, the average and spread of word lengths; Voynich words almost never exceed ~9 letters. Top-100 coverage, what share of all running text the 100 most common words account for, a measure of how concentrated the vocabulary is. Near-twin network, the share of word types that differ from another word by exactly one letter (explained in the model section above). Layout constraints that need a full manuscript to measure (line-final m-words, paragraph-initial p/f gallows, the grammar consistency r ≈ 0.55, line-bound recurrence) are listed in the report with their measurement code.
Questions everyone asks
Honest answers, no hedging
What does "EVA" mean, and is it the same as a translation?
No: EVA (Extended Voynich Alphabet) is just a way of typing the manuscript's glyphs using ordinary keyboard letters, so researchers and computers can work with the text. When this page shows daiin or qokeedy, that's EVA, it tells you which glyphs are on the page, exactly like writing "alpha beta gamma" tells you which Greek letters are written, without telling you what the text says. A transliteration is a map of the shapes; a translation is a reading of the meaning. We have the first. Nobody has the second.
How would you even pronounce a Voynich word?
You can't, really, the glyphs were never matched to sounds. EVA letters were chosen for visual resemblance and typing convenience, not phonetics (the glyph transliterated "k" doesn't necessarily sound like an English "k"). When people "read aloud" Voynichese in videos, they're picking a pronunciation, not recovering one. That's a choice, not a discovery.
Has anyone ever decoded even a single confirmed word?
No. Several specific words have been proposed as labels for plants or stars (this page tested some of the most prominent, including the "Pleiades" star-cluster label and zodiac day-number readings, both Part 51/52, both inconclusive or falsified). Zero proposed word-meanings have passed independent, blind verification. If one ever does, it would be major news, not a quiet footnote.
Is it a hoax?
Maybe, and that's a serious scientific position, not a dismissal. A fitted mechanical process reproduces nearly the whole statistical fingerprint, and the only long-range structure in the text is drifting habit, which is what unconscious human production looks like. But the book is also expensively made, internally consistent for ~38,000 words, and organized like a reference work. "Elaborate meaning-free artifact" and "hoax" are not quite the same thing.
Why can't modern AI just translate it?
Translation needs either a key, a bilingual text, or enough meaning-bearing long-range structure to anchor on. The Voynich has none of the three, we measured the third one directly (no discourse-scale information, Part 56). AI can generate plausible-looking "translations" of anything; that is exactly why our falsification lab exists. Any claimed translation, human or AI, must reproduce the measured constraints first.
Is it aliens / magic / a lost civilization?
No evidence requires anything exotic: parchment radiocarbon-dated to the 1400s, iron-gall ink, European book construction, five identifiable scribes, and statistics a medieval copying process can produce. The mystery is real, but it is a human-sized mystery.
What would change your mind?
A key found in an archive (we published a ranked search plan); a bilingual fragment; or any proposed reading that passes the falsification lab above. We also list the experiments that could kill our own current picture, see open problems.
Who funded this? What are the credentials?
Nobody and none, this is the independent, unfunded work of a curious amateur (with AI assistance, disclosed). That is exactly why everything is open: the data, the code, the failures, and the standards are the credentials. Rerun any number on this page yourself.
Free tools: take everything
Every tool, free, no dependencies
All code is plain Python 3 (stdlib only, if you can run python3, you can rerun this investigation or point the tools at your own theory). The report documents every experiment including the failed conjectures. Data sources are linked rather than redistributed where licensing is unclear. Start with INDEX.md, the map of every document and script.
Not a programmer? Start here: the Full report is the readable version of everything below, every chart and table on this page links back to a numbered "Part" in it. If you just want to see the evidence, read the report; the scripts exist so anyone can check the report isn't making the numbers up. Roughly: files starting audit_* and decipher_* are the hostile/adversarial tests; *_test.py are the individual experiments referenced by the ledger and audit tables; canonical.py and generators.py are the shared plumbing everything else builds on.
Voynich transliteration: Zandbergen–Landini ZL 3b (May 2025), voynich.nu · Manuscript scans: Yale Beinecke · Linear A: lineara.xyz corpus · Indus: CISI digitization · Control texts: Project Gutenberg, bible-corpus, Quran-JSON.
The Voynich Project is maintained by Burak Genç, independent researcher. Prior work this builds on and credits: Currier (languages A/B); Bennett 1976 (entropy); Stolfi (word structure); Montemurro & Zanette 2013 (topic information); Timm & Schinner 2020 (self-citation generation); Bowern & Lindemann 2021 (linguistic survey); Lisa Fagin Davis (scribes); Rao et al. / Farmer et al. (Indus debate).
Open problems we left on the table
For anyone who wants to pick up where this project stops, six concrete next steps, in our own words:
① Syllable-value search, done (Part 64): null against search-matched scrambled-lexicon controls; the last internal route is closed, and the ~57–74% null hit-rates measure exactly how convincing a wrong "translation" can feel. ② Takahashi-transcription replication of the new Parts 54/56/58 results. ③ Hand-proofing the OCR-mined Cuman corpus against Kuun's printed pages. ④ A true medieval list/inventory corpus (account books, litanies) for the long-range genre axis. ⑤ The key, if it exists, is an archival object, the Kircher correspondence and Rudolf II inventories are where provenance points. ⑥ Everything here deserves hostile replication; the falsification lab above is the bar we set for ourselves too.
