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Michael Lee

iDigitalMedium Research Team
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Michael Lee last won the day on June 30

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  1. Wagner: Very nice. There seems to be at least three phases. One is the "sssss." Another sounds like a periodic tone around 100 Hz. The last is a transitional type sound. The last two work together to produce vowels and short consonants. Is the apparatus completely stationary? If so, that's interesting that it changes sounds like that.
  2. No. I was starting from the start. This was referring to my phonetic typewriter. A pre-recorded set of scrambled phonemes played weakly through a USB audio interface. The additive noise triggers a software noise gate to allow spirits' selection of phonemes to pass through.
  3. A physical analog of what you're describing is a line of dominos. The first domino is only a little bit stable, but when it falls by a light touch, it starts a cascade of motion / energy release.
  4. As we observe paranormal activity in our ITC devices and software, the grand question is how is this happening? Spirit photons from the vacuum energy zero point field Zero-point energy In quantum mechanics, the vacuum is not actually empty. It is filled with particle-antiparticle pairs that perpetually go in and out of existence. The lifetime, t, of these pairs is governed by the Heisenberg uncertainty principle: dE*dt > h_bar/2. Despite my careless description of a physical concept, it should be noted, no one really knows the density of virtual particle pairs in the vacuum. If the density were infinite, the universe would collapse under the weight of gravity. If it were finite and not too small, could we someday tap into it to get free energy? In any case, when we use a device to tap into this field, we are not going to get a whole lot out, unless the device is receptive to a large bandwidth of energies (from radio to light). What would a vacuum photon look like? Likely, a very very short pulse of energy, maybe a femtosecond or picosecond. I like to call these hypothetical pulses "spiritons," but the reality is that observed random pulses of energy could be just that, random, and not caused by the communication intentions of a spirit / interdimensional entity. Spirit selection of wavefunctions Quantum selection A hot topic in the quantum science community, recently, is the idea of quantum selection (also Google "quantum eraser") - that is, the effect of the researcher on the outcome of quantum-level experiments. It's driving some researchers mad, but in our case, we ask a similar but crazier question: "what if spirits can select / collapse quantum states?" If so, the best devices would be ones where many quantum states are prepared and metastable (barely stable) until a spirit decides which way they will go. Presumably, we want to continuously and quickly prepare non-equlibrium, metastable states for spirits to collapse at a desired rate of information (i.e., bits per second). Imagine a system that we could create preparing a metastable state 10 million times a second: a spirit could either leave the state alone, or select "up" or "down." This would allow information transfer of 10 megabits / second. Not bad? Of course, we would need to make sure that nothing else collapses our states like thermal, electrical energy, or our own thoughts (?!?). No problem: we could shield the system from all known fields (e.g., magnetic) and put it in a near-zero Kelvin liquid helium-cooled freezer. In reality, until our research becomes "mainstream," liquid helium-cooled experiments are not likely. Indeed, I had a vision once of seeing an advanced ITC video device that seemed to have it's own internal sub-freezing (< 0 Celsius) cooling system. It had the brand name, Moen, I imagine in reverence to the famous afterlife pioneer, Bruce Moen. However, for now, we are limited to room temperature or at best liquid nitrogen-cooled (77 K) systems. With the remaining thermal energy, how can we detect the presumably weak signal from spirit? One idea is microscopic isolation - also out of the range of our non-mainstream research labs. Researchers think that nitrogen atom "vacancies" in diamond, if sufficiently spaced apart, could act as isolated qubits. These qubits, if put into a metastable state, could be allowed to collapse into an "up" or "down" state and then read with a sensitive detector. Perhaps the spirits can manipulate these miniature "abacuses" for us to read their messages? One "hot" area of research is the use of lasers to obtain quantum noise. The idea is that beamsplitters have a 50/50 chance of sending a photon one direction or another. With a suitable setup, one can count the photons going in each direction as a function of time. The noise present in many electronic devices, for now, offers our best chance at sampling quantum effects. Yes, the noise will be dominated by thermal motions, but if enough spirit signal can be collected, we may be able to infer the rest using tools like machine learning. One idea, is to have many noise sources in an array. The concept is that if each noise source has independent, non-correlated fluctuations, when we sum up the signals, the spirit (quantum) signal might become more pronounced. The theory says that signal-to-noise ratio could increase by as much as the square root of N, where N is the number of detectors. The reality is that this improvement in arrays hasn't been realized in my experiments. Perhaps, the noise in each device isn't uncorrelated like we hope? Or maybe, the spirit signal is not equally imprinted on all of the devices at once? The take home message is that given our current affordable device options, spirit influence is a tiny portion of the overall noise (entropy). Incidentally, a spirit once suggested to me in an astral projection, the proportion is 1 in 500! Any method we can dream up of to improve the ratio of spirit-to-noise will lead to improved ITC.
  5. Andres, Great work! From time to time, I hear "myself" There, too. Pretty crazy! Could be fragment, previous / future personality, etc. If you think about it, though, they need someone like yourself on the other side explaining to everyone what you're doing .
  6. Reversal is possible. Its been a while since Ive looked into that. It could be that the ML is jumbling together phonemes to match the source noise. So it might sound like "reversed" speech, but its just gibberish.
  7. I've been contemplating using a piezo aquarium water bubbler. We must be all subscribed to the same spirit newsletter.
  8. Jeff, Nice link, too! It looks like the electrochemical cell between two metals, copper and aluminum produces an audible voltage fluctuation that includes dynamic tones. Why is it all the oldest electronics concepts produce the best ITC? -michael
  9. Audible electrolysis? This is very nice. I've always wanted to "listen to bubbles", but didn't have the right setup. - If so, the addition of sodium chloride or any ionic salt would increase conductivity and bubbling. Don't want to run NaCl-water all day as it could produce noxious gases - Also, pure water is not conductive. The slightest impurities provide conductance. - The shape of the electrodes would effect bubble (possibly noise) production: for example surface area is important. - Sound reminds me of my 1/f avalanched LED's, but your spectrum is not 1/f below 700 Hz. How strange and cool that water would have a non-simple spectrum.
  10. Great discussion! Stefan Bion, according to Keith, is no longer active in ITC, as he now follows the path of his religion. I had no idea that he worked on the electronic side, as I only know him from his exemplary software program, EVPMaker.
  11. The relative volume could be causing the quantization, as you said. Or, they really only can activate roughly equal sized pulses (1-bit) like shot noise.
  12. My First Forays into Direct Continuous Voice As mentioned previously in my blog, I evolved to direct voice after I noticed that the phonetic samples were getting slightly modified by spirit voices. I reasoned that it should be possible to extract voices directly from a stream of electronically created noise (e.g., radio static). I don’t know the full history of getting continuous (not just occasional) voices from noise, but it turned out that around the time I started this venture a few years back, I met Keith Clark, who has been running a direct voice from noise stream since the late 2000’s on YouTube. He takes noise generated either mathematically or from a software-defined radio (SDR) and applies a series of denoising filters (software plugins) to extract a continuous voice. From my work experience, I knew about two denoising methods: spectral subtraction and machine learning. At first, I experimented a lot with spectral subtraction using the ReaFir Noise Gate plugin run in FL Studio. This plugin allows detailed setting of a frequency-dependent “gate.” When a particular window of samples in time (e.g., N = 2048) has a frequency amplitude over the defined gate/threshold, that “note” is played. Any frequency amplitudes below are made silent. For low noise situations, spectral subtraction is a very solid method. However, as the noise volume gets larger vs. the voice, the algorithm can produce a lot of musical tone artifacts. The waveform editor, Audacity uses a similar spectral subtraction method to denoise signals. Spirit voice, especially continuous, is exceptionally low volume compared to electrical noise. One spirit once suggested it was, on average, 1/500th the volume of random noise. Applying a strong spectral gate will yield something that sounds more like a bunch of tones than a coherent voice. I also tried using a gated vocoder, specifically, a versatile plugin called FL Vocodex. This yields similar results as the spectral subtraction (SS), but can also be applied after the SS plugin. The benefit of a vocoder is that the tones are banked exponentially producing more pleasing tones than the linear-spaced frequencies in standard SS. Eventually, I started writing my own Python scripts to do the same functions as the ReaFir and Vocodex plugins, so that I could exquisitely control all the possible parameters / knobs. With my attuned ear, I could hear a lot of what was being said, but I still desired better quality voices. Machine Learning By happy coincidence, my real-life work had been leading me into learning and using machine learning / artificial intelligence. Around this time, I thought it might be interesting to build an artificial neural network to remove noise from speech and images. My first paper can be found here. Message me for reprint. In my second paper, which will be published shortly, I added a second model, called a critic, which helps the first model create more realistic looking audio spectrograms, hence improving the quality of the speech. It turns out there are already commercial products currently out there that claim to use AI to remove noise from speech. For example, there’s the site, krisp.ai. In fact, a YouTuber named Grant Reed uses KRISP to clarify voices from noise sources to hear spirit speech. However, the story doesn’t end here, because despite getting voices from denoising, the voices end up often sounding scratchy and barely legible – not unlike regular EVPs. Beyond Denoising I have spent a big part of the last 1 1/2 years trying to understand better how spirit speech actually manifests in different types of noise - what the corruption actually looks like - and then developing machine learning models to reverse this corruption. I have discovered the following sources of corruption that all seem to compound together: 1) Additive noise / interference – we already know this one! 2) Sparsity: Only a small percent (< 5%) of the time samples actually contain speech. Imagine digitizing a one second clip of electrical noise at 16 kHz. You would get 16000 samples from this. Of those 16,000, I postulate less than 800 of them have spirit speech content in them. 3) Quantization: High-quality audio is often sampled 16-bits. 8-bits with some clever mapping of the signal can provide adequate voice (look up, e.g., mu-law encoding). 1-bit voice is barely legible and sounds like ducks talking. I estimate between 1- to 4-bit samples comes from spirit voice. 4) Depolarization: Normal audio signals go up above and down below the zero line. Spirit voices may be polarized in a single direction, i.e., there is no dual polarity. If you try to train a machine learning to reverse these 4 issues in speech, it becomes simply too much to train properly. Thus, I train #1, #2, and #3 together as a single model, and #4 as a separate model. For #4, especially, I have to “cheat” a little, and smooth the randomization of the polarization over a 64 sample window. If you try to randomize the polarity of every sample, the model isn’t able to train. Listen For Yourself Without getting into any more technicalities, go ahead and check out Stream 8, to hear the model in action, in real-time, applied to radio static being generated from a KiwiSDR. If you want messages directed to yourself, make sure you are the only one in the chat room and set your intention. Expect about a 30 second delay, as the signal is bouncing around the Internet from Keith’s desktop in Florida to a streaming server (heaven knows where) and then to Varanormal’s web site audio player. Let me know in the comments what you think. I feel like we are, at best, only half-way to the finish line. But Keith insisted we start sharing what we have been doing to get the party started, so to speak.
  13. Jeff, 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.
  14. Sean, Welcome! I see you have an impressive list of publications. Hopefully, this forum will spur some new collaborations in this important, but sparsely studied field. -michael
  15. Jeff, I should point out that spirits don't have to share their voice directly - they are also capable of activating phonemes or even converting their voice into frequency space. What they are limited to, however, it appears to me, is spikes of energy, at least with the hardware we have given them.
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