EVPs are disembodied voices on found on electronic recording devices. Some believe these to be ghosts, while other explanations say they could be alien, interdimensional or even psychically created by the living (EVP-type phenonmenon). Some argue that they are radio waves, yet there is no explanation for intelligent responses. However, there has been discoveries to link EVP to EMF and frequenices beyond human ability.
EVPs are often classified as A, B and C. Class A EVPs are very distinct and very clear. Class B EVPs seem to clearly be voices, but people interrupt them differently as it is not clear what is being said. Class C are unintelligible and might even be called into question if it really was a voice. In these class you especially have to be aware of auditory pareidolia, a psychological effect where random sounds are interpreted as voices.
They can also be classified by source (gender, age, human, animal), vocal / non-vocal, speed (normal, slow, fast, reverse), content (surrounding specific, general statements, gibberish, utterances).
1. Here is an example of a very odd EVP. Three males are present in the room. There is what appears to be a voice that sounds like someone fast forwarding a tape recorder. When this is slowed, it appears to be a woman's voice. This comes from a location that we have investigated multiple times and have caught many strange EVPs.
slow speed version
The file was a total of 8.134 seconds. I analyzed between 3.792 to 4.605 seconds.
As with 23, this recording yielded some interesting results. The pitch file will show similar correlations between consistent higher energy and higher frequencies toward the top of the graph. You should take note of the distinct purple across the top. It show distinctly high pitches.
The spectrogram shows the same thing - increasingly high energy levels with increasingly high frequencies.
2. One of our favorites from Miss Molly's B&B. One person makes a statement about dancing, and an unusual voice with an accent makes the comment " I hate dancin!" (Both voices are EVPs). This is an example of a class A. This is the EVP that they refer to on TV show Ghost Lab. Everyday Paranormal also caught an EVP that talked about dancing.
The recording was 10.527 seconds long. I isolated and analyzed the recording between 7.864 to 9.484 seconds. "I hate dancing" is clearly audible. There is a long "i", long "a", and short "a" with a "n" sound. The graphs reveal this information. The pitch file reveals the increase in pitch and frequency in three key areas, as indicated by the second file (pitch box).
The three words are between 8.038 to 8.284. 8.539 to 8.805, and 8.893 to 9.484 seconds. The "voice" appears to be a younger female - perhaps around ten years old or so. She emphasized the word "hate". Further research is warranted to establish a correlation between the voice, words, and the location itself.
On the spectrogram boxes file, you will see the areas of the three words in the black boxes... "I...hate...dancing". There are clearly spikes in frequency and decibel levels with "hate" seemingly the highest in terms of decibel level.
3. We use recording equipment that enables us to listen in real time through headphones. Imagine my suprise on the first EVP I caught live. Again, class A EVP.
The total file length was 13.759. I analyzed between 1.998 and 3.207. I have begun included the x and y axes within the analysis photos so you know what you're looking at. "Help me" was clearly audible and the reaction of the investigator seems genuine.
4. Carter ghost town. This one is a bit creepy. The first voice you hear says "show me where I kill her" - it is not one of our investigators...later you will hear, "show me where I hid her" and a laugh at the end. Again...not our investigator!!
5. Texpart captures a voice that verifies what the resident owner claimed to have previously heard.
6. Hill House Manor - what a strange place this is. These EVPs occurred together within a one minute time period. EVPs continued to occur for about the next ten minutes, in what sounded like intercourse, but the EVPs grew faint.
Here is a youtube link. One of the EVPs was captured in the next room, on this DVR camcorder.
7. "she died ...."
8. "go now"
9. "can somebody help me"
The file was a total of 4.318 seconds. I analyzed between 0.997 to 3.067. I also there is an AI between 2.699 to 3.067, which I believe to be saying "now".
There's something interesting to be said about the spectrogram. I have attached three additional files to compare with your spectrogram. The software program I use can generate the three different types of noise - white, pink, and brown. When we say something is "white", it just means refers to a type of noise generated as a result of the way light works. White light is made up of light of all different frequencies. White noise, then, is produced by the combining of sounds of all different frequencies together. Pink and brown noise both have more energy at lower frequencies while white noise has equal energy to all frequencies. I have included a sample of all three as additional files.
The reason is because the spectrogram is showing striking similarities between these and the recording itself. The spectrogram shows a considerable amount of energy and many frequencies, which is highly unusual based on what I've seen so far. The spectrogram of the brown sample seems to be the most closely related to the spectrogram of your recording.
There's something interesting about that because I've conducted experiments with brown noise that have yielded incredible results. Many of the recordings with brown noise result in, what I can only describe as, multiple conversations.
Your recording shows a relatively even distribution of energy and higher frequencies. It indicates "intelligent manipulation" of the frequencies. I was really surprised to see such consistency.
The pitch files was the best at being able to show where the intensities occurred. The different peaks in small areas of purple toward the top indicate the highest intensities and the highest pitch. In addition to being one of the best representations in the spectrograph, the pitch is by far the best I've seen to date. I was actually really excited by these findings.
10. we think it says, "are you here to kill me bill."
11. "....more comfortable and quiet here"
12. Two female investigators went into the room. JJ says " I think I will sit on this bed and take off my boots. A male voice responds "take um off!"
Here is the shorter version.
The file was a total of 41.832 seconds long. I analyzed between 39.035 to 39.815 seconds. There's a distinct "p", short "i", and "k" with the first word, which I agree sounds like "pick". "Em" is clearly audible. There is a short "u" and a clear "p" with the third word. I agree that the phrase sounds like "pick em up". The short "i" with the first word is emphasized by being drawn out over many frequencies from approximately 39.040 to 39.330. "Em" is from approximately 39.333 to 39.496. "Up" is from approximately 39.496 to 39.815.
Pitch shows three AIs, high pitch for all three words. The spectrogram shows the correlation between the high pitch and the high frequencies. I should have placed the boxes around this file but didn't. Not sure why. But you should see the three distinct areas of purple mixed with blue toward the top. These purple areas correspond with the areas of the black boxes in the pitch file.
From 2828 Hz to 5458 Hz, there is a clear gap in which these appear to be little or no frequencies manipulated. This is also correlated on the frequency analysis of the plot spectrum but that file is not included. I can send that if you'd like. It was not included because it was already corroborated by the spectrogram, which shows little to no energy.
Historic McKinney Courthouse (MPAC) 2010.
14. "brother murdered"
15. While listening live through headphones, and going upstairs at Hill House Manor to check on a camera, I get the creepy sensation that someone is in my personal space. So I make some noise to distract myself, only to be mocked.
16. From UNT's Bruce Hall
Much more to come! Please check again.