Synchronous random number generators PRNG

Let's look at several ways to create software random number generators using external digital streams and without them. Let's write source code for Android Java - prototypes of applications showing the reality of using algorithms.

Generator of "random" numbers using expansion of source information, sampling and correction of source data. (Czech Entropy Application)

We will use TTS technology in this generator - converting the entered text into speech. This option is available in the Android operating system. TTS allows you to significantly increase the volume of data (30-100 thousand times), use different settings to obtain different digital results, ensure repeatability of the results (which makes it possible to build a PRNG), the transformation is “formulaless”. The disadvantages of the algorithm are obvious: the result is easily repeated (if you know the source text), large but not infinite expansion of the data, unstable level of entropy in the obtained data. Because the received data is a sound file, it may contain many repeating and dependent sequences of numbers.
Let's consider possible options for compensating for the shortcomings of such random number generators.
You can come up with (invent) quite a few algorithms for improving the results of such data expanders.
TTS conversion of the entered text several times with different parameters: sound quality, pronunciation speed, male/female voice, timbre, etc. With subsequent mixing of data from several sound files. The complexity of mixing algorithms directly affects the result. For example, you can "reverse" data in one or more audio files before mixing, introduce data shifts, block permutations, etc. At the same time, the repeatability of the results and the possibility of constructing synchronous generators of “random” numbers are preserved.

https://docs.google.com/document/d/1KVdnGEbI1_Fc45BrVEa4XQeaRATy4ynjQg5Y9yWrBAo/edit?usp=sharing

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Android PRNG
Android application developer Java - synchronous software random number generators and their algorithms: based on external flows, based on formulaless expansion of source data, based on data accumulation, using feedback, neural networks, with controlled quality of entropy, up to the ideal distribution of numbers . https://www.linkedin.com/in/valery-shmelev-479206227/

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