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This is very interesting Michael...can we get the link in here to the other post where the instructions are? I think its great! Would love to try it myself as soon as I get a break. 


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A very cool video Michael. Now I fully understood the basic principles of noise gating. A step further would be to separate scrambled voice and noise from each other thus the noise is gating the voices without being recorded.

Another idea came to my mind. One could fo a similar approach just with the level controlled recording feature in Audacity that actually could do the gating. A downside is the fixed lag-time in Audacity but it would be worth a try.


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Yes! We could feed the noise and signal through separate channels like L and R. Then, the signal would be clear as a whistle.

I haven't tried this, yet, but it should doable in my scripts.

One of the caveats I can see is that there may be a little magic (like voices coming through the noise, or signal manipulation) that we would lose.


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This is true. The question is if the spirits would agree to adapt. On the other hand multiple voices often interfere even in pure noise, what makes listening to them a challenge. This problem we are facing generally with every technique that gives a continuous stream of voices.

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What a great process you've created here Michael. The segmented audio blocks remind me of radio sweep, but without the two main disadvantages / pitfalls, which I was in process of engineering out when I was working with radio sweep.
Firstly, your fast scrambling of carrier audio prevents the false positives of source words being partially (or fully) heard when using longer segment lengths, and secondly, with the use of noise gating, you have 'true' (very fast rise time and decay) blocks of audio, instead of the bell shaped audio amplitude "blips" that plague radio sweep, due to the (usually poor) selectivity curve of the receiver's front end and IF stages. In my opinion, it is this aspect of amplitude dynamism that holds magic for the transformation process.


P.S: What program do you use for scrambling the audio track?

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Because the stream of phonemes is fixed (just playing a WAV file) you can compare different runs to see if you're getting different messages. If you're getting the exact same messages each time, then you know the gate isn't set correctly, etc.

I generate the scrambled phonemes with my own Python script, which I've shared here. It ensures that each blip is the same magnitude and clipped so that, in theory, none of them should trip the noise gate without help from an extra noise source.

Getting Python scripts running on your machine requires Anaconda3 and a few module installations, but at least you can see the general idea of what's going on.


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Thanks for sharing this with us Michael, and the other scripts too. It is generous of you. I have no experience with Python, but will get it sorted.


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No problem. We have a technique for converting Python scripts to executables. The caveat is each one takes up 700 MB on the user's hard drive. 😬

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Michael, Im not sure if youre going to take the noise gater further (re separating the noise and carrier into left and right channels), but I had some ideas come to me regarding it too. I will list them as a process. You may have already tried or thought of these, so apologies if you have.

1) Adjust noise gater set up parameters, and level of noise/signal input (from phone) for best / most prolific reception of voices.
2) Measure the average timing mS periods of mute and unmute durations as generated by noise gater.
3)Create a switching waveform that emulates these periods as 2 average static values of mark and space, OR a waveform that dithers between the min and max values observed for each of mark and space.
4) Convert noise gate to a simple audio gate with a mute/unmute control input, and feed above waveform into it. Observe results.
5) Compare (1) with (4) to see if the synthesized gating (not using noise based decision) is just as effective as noise derived gating.
6) Increase level of carrier from phone so level is high with no noise, but then attenuate output, so result is back down to the level of the original carrier level (low) when it was mixed with noise (so magic hopefully isnt lost). Use this as the carrier input.

It will be revealing to see if this method has merit, and will teach some new things about the process.



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Generally speaking, I haven't spent much time on the phonetic typewriter as I've switched to machine learning assisted "direct voice." However, I agree with you that this work does subtly reveal the abilities and limits of spirit influence for a given hardware system. 

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