25-06-2025, 10:18 AM
(25-06-2025, 09:04 AM)oshfdk wrote: You are not allowed to view links. Register or Login to view.Why so? As far I as know, Voynichese entropy is relatively low only for short ngram values, like bigrams and trigrams and gets much closer to normal with the increasing length. This is exactly what happens in the original graph at the top of this thread.
Ah, I see. So you have a sliding window of n, and then you see how well you can predict the next n characters? I just can't intuitively grasp what this tells us. It's too abstract - a measure of the information density of the writing system.
When it comes to conditional character entropy (next character), it's easier to explain to a general audience what's going on:
* given a letter from a random English word, you can't easily predict the next letter. For example, with "s" as the first letter of the pair, the distribution of the second letter is quite even, and you have many options to choose from.
* In Voynichese, the opposite is true: given any glyph, you have fewer options to choose from for the second glyph (because of positional restrictions etc.), and the distribution is skewed towards one or a few most likely options (low conditional character entropy). EVA makes this worse by chopping some glyphs in half, artificially creating very frequent pairs.
When comparing larger n-grams, this intuitive aspect of it is gone: you are just looking at information density as an abstract number.