Michael Lee

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.

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 .

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.

I've been contemplating using a piezo aquarium water bubbler. We must be all subscribed to the same spirit newsletter.

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

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.

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.

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.

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.

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.

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

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.

The general method is to figure out how a spirit voice is corrupted when we hear it directly from our noise-generating devices and then train a machine learning model to reverse the effect. Specifically, I have found at least three corruption processes: (1) the spirit signal is often heavily buried in noise (i.e. additive noise). 2) the spirit signal is "quantized" or in other words it sounds like it's (e.g.) 2 to 4-bit audio vs. clean 16-bit audio. 3) the signal is "sparse" or missing a lot in time - instead of hearing a smooth waveform, we are randomly getting 10-20% of the time samples, instead of all 100% of the samples. So, what you do, is you train a machine learning to convert clean English speech corrupted by these three processes (or others) back into uncorrupted clean speech. Then apply this trained model on your favorite noise ITC signal. It's been a struggle because I think these 3 processes together (and others we don't know about) are just too destructive on the original audio that spirits are trying to convey. In other words, we lose too much information to restore back to intelligible speech. We are always on the lookout for more spirit-sensitive hardware.

Here's some "greatest hits" from the last year : youre_getting_good_voice_now.wavtotally_fine_with_us.wavsuch_a_great_signal.wavthis_is_so_exciting.wavisnt_portal_so_fun.wavstop_mixing_it_directly.wav

Jeff, Although a little off topic from the original question, I agree with your understanding that spirits utilize the sounds available to them. This can actually be stated mathematically as convolution: roughly speaking they can slightly change the volume of the individual frequency components of environmental sound. I recently experimented with two microphones and several projected sounds (testing one at a time) from a speaker. Then using microphone cancellation and machine learning to disentangle the original voice. I like to think of the played sound as having two functions: 1) provide a fixed sound field that we can accurately and mathematically (digitally) remove from the recording. 2) energy for spirits to manipulate, like your thoughts suggest and my convolution theory. I agree with you that locality may not be all that necessary for spirits. Ill tell you though, it would help with isolating out the sound pollution in my household.

One technology that the commercial space has been exploring is microphone arrays for smart devices like the Amazon Echo. The idea is that multiple microphones better cancel out environmental noise and reverberation leading to a clearer voice for speech recognition. What would be the benefit for ITC? Localized spirit voices? Improved signal-to-noise? It's not easy to make a microphone array, so the argument for pursuing this would have to be compelling. BTW, I have played with two microphone setups. This is easy to do and does help with sound cancellation if there is a localized audio source.

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.

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. phoneme_scrambler2.py

Yes. I assume it's the point where the current is in between saturation and zero.

Although I don't know if it's that good of an ITC entropy / noise source, I think it is pretty cool that we can actually hear the flow of photons from a laser or flashlight. Simply make a circuit of 48V (phantom power) -> 10K resistor -> PhotoTransistor (PT) -> Gnd (audio interface output). I use a BPW85A (purchaseable from Mouser for ~$1 each) Turn off all the lights Take a continuous light source (either a bright flashlight or pen laser) and point it at the PT face. Then slowly turn it away. You should hear a click sound as the voltage goes from high to near zero. Then, carefully adjust the light until you're getting lots of clicks. You should hear what sounds like pink or white noise if you get it just right. I think this noise is a stream photons hitting the phototransistor and generating a current that is neither saturated or not registering. This noise can be "filtered" with denoising, etc. to obtain spirit voice, but as I said at the outset, I don't think it's the most productive medium for spirit voices, likely because it stems from the noisy circuitry of the light source. One could imagine fancier light fields with mirrors, more than one light source, absorbent materials, water, smoke, etc.

The corona noise is a decent source for ML input but nothing extraordinary. It could have a quantum component due to reflectance/transmittance of the laser lens, but it could also have a noise component due to the driver, which is commonly considered to be more classical electrical noise (however, that's up for debate!). I had a delicate setup with two PDs at 90 degree angles of a beam splitter, that also yielded voices in ML. Maybe we could develop a "pocket" vibrometer for ITC/non-ITC use? It could be a better microphone in terms of sensitivity and locality. I was even imagining using something like guitar strings as vocal cords where the laser could pick the near still vibrations. A parabolic mirror could be used to ensure all the rays return back to the PD.

Two more things Ive observed today. The laser shot sound is known as laser doppler. It is a type of interferometry where the beam reflects back on itself, yielding the ridge patterns, that with movement of the reflective material, creates a fast washboard effect. It is most easily achieved by shining the laser directly into the phototransistor and lightly wiggling the laser. The other thing I noticed is that my pen laser has an incoherent corona around the beam, that I can hear by pointing the beam just off center from any direction to the phototransistor. Its a mix of pink and white noise. It may be a good source of spirit voice, but I need to amplify it more, so we'll see.

To add, my blog is slowly walking through the noise conversion methods in my software. Simply put, I can turn anything into voice-like sounds. Now we have to listen closely and try to understand what they are saying and see if they are giving us advice on how to proceed.

Andres: I've set up a system that makes yours look like a final product . A few quick notes: I think one of the explanations for some of the sounds we're hearing is laser vibrometry. The idea is that the minutest of vibrations, displacements, and temperature changes have large effects on the intensities and interferences that are then audible. Different materials have different reflectances, vibrational modes, and temperature-based motions. Imagine for example shining a laser on a vibrating string. I'm able to almost tune in the laser shot sound but have no idea what it actually is coming from. From what I've read, the lower the power for a given laser, the higher the ratio of quantum to classical noise.

Good points! Spirits in my stream often use the term "entropy" The concept here, I think is that some things are deterministic like the laws of physics or a mathematical formula that generates pseudo-random numbers. Other things are inherently unpredictable - no amount of observation and modelling will ever achieve a correct prediction of the future state. It is in that unpredictability that entropy and, indeed, free will (of both us and our spirit friends) exists.