About the generation of similar words

[quimqu]

I’ve been trying to answer a simple question: are Voynich bursts just the same thing we see in normal language, or is something structurally different going on inside them?

First thing. Bursts are not unique to the Voynich. If you run the same detection on normal texts, you also get bursts, and they also show some local structure. So just saying “the Voynich has bursts” is not enough.

The difference shows up when you remove short words and keep only tokens of length ≥ 3. In normal texts, the burst signal drops a lot. In the Voynich, it barely changes. That already tells you something important: in natural language, a big part of the burst effect comes from short, frequent words. In the Voynich, the structure sits in the main vocabulary itself.

Then I looked inside the bursts.

In the Voynich, the real order of tokens does three things compared to a shuffled version of the same bursts. It creates more local parent-like matches, those matches are closer in sequence, and the words are slightly more similar to each other. In natural texts, you only see the first two effects, not the third. The real order does not make words more similar than shuffle.

That’s a key difference. Voynich bursts are not just clusters of similar words. They behave more like a local walk through nearby variants.
I also checked directionality. If this was a simple chain where each word generates the next one, you would expect the best match to be more often in the past than in the future. That does not happen. Not in the Voynich, not in normal texts. So this is not a simple left-to-right generation process. It looks more like a dense local network.

The most interesting signal comes from looking at triples A → B → C inside bursts.
In the Voynich, you more often see small step + small step = bigger step patterns, and you also see a stronger tendency for length to grow or shrink consistently across two steps. In natural texts, what you mostly see are compact triangular families, which is exactly what you expect from normal morphology.

So the picture that emerges is quite different.

Corpus	Burst share (len ≥ 3)	Key observation
Voynich	0.6877	Most of the text is inside bursts, even without short words
Culpepper English	0.2707	Bursts exist but depend more on common short words
De docta ignorantia Latin	0.1613	Weaker burst structure overall
Alchemical Herbal Latin	0.0675	Very limited burst behavior

Corpus	Real vs shuffle (similarity effect)	Interpretation
Voynich	Real order makes words more similar	Local sequence pushes toward nearby variants
Natural texts	No similarity gain vs shuffle	Clustering exists, but not sequential transformation

Corpus	Radial chains (A→B→C)	Compact families	Length monotonicity
Voynich	Higher	Lower	Much higher
Natural texts	Lower	Higher	Low

So I wouldn’t say “bursts prove the Voynich is special”, because they don’t. But once you control for short words and look at what happens inside bursts, the behavior is clearly different.

Natural texts look like clusters of related forms. The Voynich looks more like something moving step by step through a space of very similar variants.

That doesn’t prove a specific mechanism yet, but it does narrow things down quite a lot.