Generating Text Watermarks Using AI Prompts

The idea of ​​using "text watermarks" (digital watermarking) to protect copyrights through linguistic patterns is a truly promising and profound approach. It is much more complex than conventional steganography, as it requires preserving the naturalness of the language (perceptual transparency).
According to statistical studies of Russian speech (for example, data by V.N. Elkina and L.S. Yudina, as well as analysis by Stefan Trost Media), the most frequent syllables are open syllables of the SG type (consonant + vowel).
Below is a list of the 10 most frequently occurring syllables (two-letter combinations that most often act as full syllables or their stems) in Russian texts, along with their approximate share:
Place Syllable Approximate Frequency (%)
1 TO 1.72%
2 ST 1.55%
3 NO 1.46%
4 NA 1.42%
5 NI 1.25%
6 KO 1.25%
7 NE 1.23%
8 EN 1.22%
9 PO 1.16%
10 RA 1.13%
Brief Analysis of the Technology:
Dominance of "O" and "A": Syllables with the vowels "O" and "A" form the core of Russian phonetics. Grammatical factor: The high ranking of the syllables TO, NO, NA, PO is explained by their presence in prepositions, conjunctions, and demonstratives, as well as in verb endings and suffixes (e.g., ЕН, СТ).
Structure: Open syllables (ending in a vowel) predominate in the Russian language, making them ideal candidates for embedding tags, as they are natural and ubiquitous.

If phase substitutions are planned at the syllable level, choosing the most frequent units will allow you to "hide" the code as deeply as possible in the text structure, as their presence in any sentence appears completely natural.

Query #2

Which letters appear in Russian words immediately following syllables:

1. 'TO'
2. 'NA'
3. 'STO'
4. 'NO'
5. 'NI'
6. 'RA'
7. 'KO'
8. 'VO'
9. 'PO'

Arrange the first 10 values ​​for each syllable in descending order.

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Google AI Response

For linguistic analysis and the construction of "text watermarks," it is important to understand not only the frequency of syllables but also the most likely paths for their continuation.
Below is a list of the most likely letters that appear in Russian words immediately following the indicated syllables. The list was compiled based on an analysis of trigrams and the morphological structure of the Russian language (taking into account roots, suffixes, and endings).
The letters are arranged in descending order of frequency:
'TO'
M, R, V, L, S, N, K, D, G, P
(For example: then, which, ready, table, ethos, autonomous)
'NA'
CH, S, T, D, L, V, K, P, B, G
(For example: beginning, mood, nature, hope, tax, skill)
'STO'
YA, R, L, I, K, P, V, G, T, N
(For example: stand, side, table, cost, stock, stop)
'NO'
V, S, M, R, T, K, G, D, L, Sh
(For example: new, nose, number, norma, note, knockout)
'NI'
E, K, T, L, C, Z, M, S, V, G
(For example: mnie, nobody, thread, nil, nitsa, bottom)
'RA'
B, V, Z, D, T, K, S, M, N, P
(For example: work, equal, time, joy, ratify)
'KO'
N, T, L, R, M, S, V, D, P, G
(For example: end, cat, knee, king, room, space)
'VO'
D, Z, L, R, S, T, P, N, K, B
(For example: water, air, will, gate, east, here)
'PO'
L, D, S, R, T, K, V, N, M, B
(For example: field, under, after, port, stream, peace)
How to use this for WaterMark:
When implementing a hidden pattern, you can choose words where the "signal" syllable is followed by a low-ranking letter (for example, the 9th or 10th letter in the list). This combination will be less common, creating a unique statistical “fingerprint” of the author, while maintaining the complete naturalness of the text for the average reader.



https://t.me/llmsource/
http://oflameron.com
https://github.com/vallshmeleff/oflameron-obfuscation-language
https://androidjavaopensource.blogspot.com/
https://ailanguagesdatasets.blogspot.com/
https://12f3688e.pinit.eth.limo
https://proposed-gray-cattle.myfilebase.com/ipfs/QmXMVBgdZez4VfeKpoKKfSJ3j1oVfTHztmnvC2oYNSoz3x
https://pixelfed.ru/p/Jettman/929298265312142479