@Sam: The VMS is not so homogeneous as you suggest. With pages in Currier A in mind the pages in Currier B would also look strange.
Or see for instance the distribution of words like 'qokeedy', 'qoteedy', 'qokedy' and 'qoteedy' within the stars section:
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Even there the text is different for each page.
René Zandbergen has given a set of features on his website (see You are not allowed to view links.
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- The first character of each paragraph is one of a very small subset of characters.
- The first character of each line does not have the same frequency distribution as the rest of the text.
- With very few exceptions, the characters p and f only occur in the top lines of paragraphs.
- The second order character entropy is anomalously low.
- Words in the MS tend to follow certain word patterns, i.e. there are some weak positional rules, and fairly strong rules about character combinations.
- There are almost no repeating phrases.
With my app I only want to demonstrate that it is possible to generate a text with such features with a algorithm simulating my auto copy hypotheses. The main problem was to model human ingenuity in to the algorithm and to keep the algorithm as simple as possible. Therefore the algorithm only produces a pseudo text with features similar to the VMS. If I would generate the same text as in the VMS Emma would be right with her objection that my algorithm only reproduces the movements of the scribe.
@Job: I will publish the source code for my App. You can find a flowchart for the text generator here: You are not allowed to view links.
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