I’ve noticed some files I opened in a text editor have all kinds of crazy unrenderable chars
can it? Sure, most any arrangement of bits can be converted into some kind of Unicode text. Can it be converted to something meaningful or readable? No, some formats are plain text (.txt, .ini, .json, .html for some random examples) that are meant to be read by humans, and others are binary formats that are only meaningful when decoded by a computer into specific data structures inside a piece of software.
Yes, see Binary-to-text encoding (e.g., Base64).
Can you comment on the specific makeup of a “rendered” audio file in plaintext, how is the computer representing every little noise bit of sound at any given point, the polyphony etc?
What are the conventions of such representation? How can a spectrogram tell pitches are where they are, how is the computer representing that?
Is it the same to view plaintext as analysing it with a hex-viewer?
There’s two things at play here.
MP3 (or WAV, OGG, FLAC etc.) provide a way to encode polyphony and stereo and such into a sequence of bytes.
And then separately, there’s Unicode (or ASCII) for encoding letters into bytes. These are just big tables which say e.g.:
01000001= uppercase ‘A’01000010= uppercase ‘B’01100001= lowercase ‘A’
So, what your text editor does, is that it looks at the sequence of bytes that MP3 encoded and then it just looks into its table and somewhat erronously interprets it as individual letters.
I think you are conflating a few different concepts here.
Can you comment on the specific makeup of a “rendered” audio file in plaintext, how is the computer representing every little noise bit of sound at any given point, the polyphony etc?
What are the conventions of such representation? How can a spectrogram tell pitches are where they are, how is the computer representing that?This is a completely separate concern from how data can be represented as text, and will vary by audio format. The “simplest”, PCM encoded audio like in a .wav file, doesn’t really concern itself at all with polyphony and is just a quantised representation of the audio wave amplitude at any given instant in time. It samples that tens of thousands of times per second. Whether it’s a single pure tone or a full symphony the density of what’s stored is the same. Just an air-pressure-over-time graph, essentially.
Is it the same to view plaintext as analysing it with a hex-viewer?
“Plaintext” doesn’t really have a fixed definition in this context. It can be the same as looking at it in a hex viewer, if your “plaintext” representation is hexadecimal encoding. Binary data, like in audio files, isn’t plaintext, and opening it directly in a text editor is not expected to give you a useful result, or even a consistent result. Different editors might show you different “text” depending on what encoding they fall back on, or how they represent unprintable characters.
There are several methods of representing binary data as text, such as hexadecimal, base64, or uuencode, but none of these representations if saved as-is are the original file, strictly speaking.
Most binary-to-text encodings don’t attempt to make the text human-readable—they’re just intended to transmit the data over a text-only medium to a recipient who will decode it back to the original binary format.
I do understand I’m not able to read it myself, I’m more curious about the architecture of how that data is represented and stored and conceptually how such representation is practically organized/reified…
The original binary format is split into six-bit chunks (e.g., 100101), which in decimal format correspond to the integers from 0 to 63. These are just mapped to letters in order:
- 000000 = A,
- 000001 = B,
- 000010 = C,
- 000011 = D,
etc.—it goes through the capital letters first, then lower-case letters, then digits, then “+” and “/”. It’s so simple you could do it by hand from the above description, if you were looking at the data in binary format.
One representation of a sound wave is a sequence of amplitudes, expressed as binary values. Each sequential chunk of N bits is a number, and that number represents the amplitude of the sound signal at a moment in time. Those moments in time are spaced at equal intervals. One common sampling rate is 44.1 kHz.
That number is chosen because of the nyquist-shannon sampling rate theorem, in combination with the fact that humans tend to be able to hear sounds up to 20 kHz.
The sampling rate theorem says that if you want to reproduce a signal containing information at up to X frequency, you need to sample it at 2X frequency.
To learn more about this topic, look for texts, classes, or videos on “signal processing”. It’s often taught in classes that also cover electronic circuits.
Here is an example of such a text
That’s pretty dense reading, but if you’re willing to stop and learn any math you encounter while reading it, it will probably blow your mind into a whole new level of understanding the world.
I honestly wish I had gotten into all the science and physics of signal processing, taken calculus etc, I feel like I’ll pick up a lot of the more qualitative stuff over time particularly if I’m able to apply it in building certain apps that do some novel manipulations and obviously some of that will require me to get an operational understanding of how to put all these blocks together.
You still can. Worst case, you spend $80 now and then on a textbook. There’s no reason you can’t buy a physics or calculus textbook and just start reading it. Costs about the same as an expensive dinner for two.
Best case, you just learn it for free or for the cost of a Khan Academy membership.
You’re not limited to surface level understanding. You can develop as deep an understanding of any topic as anyone else. In fact, I would wager an adult who knows how to work can probably learn math and physics at a much deeper level than a college engineering student, if only because they can take their time and absorb everything fully.
Sounds like you might be a coder. Consider the level of code quality people achieve in hobby projects: often much better than in a professional setting because in the pro setting there’s always a time and budget constraint. In a hobby project, one can polish and polish and take all the time they want.
It’s never too late to give yourself a solid science education.
It’s been 20 years since I bought textbooks and they’ve doubled in price (now about $150 for a physics textbook).
But this one’s one sale: https://a.co/d/8zxWC8B
At the end of the day data is just binary, i.e. it’s composed of 0 and 1. What those 0 and 1 represent is mostly irrelevant to this discussion. The short version is that
01000001can meanAor it can mean that a given pixel is65/256red, or that the speaker should vibrate in a specific frequency, etc, etc.So what happens when you open a file that’s not text in a text editor? Well, some of the 0 and 1 make up gibberish, or characters that are not meant to be printed. Fun fact, you should be able do this the other way around too, i.e. open a text as an image, but again it will be gibberish, and most likely would not load since images have lots of information that relate to size, compression, etc, that if incorrect the program won’t know what to do, but because text can always be valid it will always work, although sometimes your editor might show weird thing in the places where there’s a non-printable character.
technically, yes. all unprintable binary can be resolved to 64 printable characters. but that resulting string may not be english or any human language.
But its still contains the actual data in a faithfully reproducible/useable way?
Yes. Decoding a base64 encoded string will give you back the exact original data.
Importantly though, this isn’t what you’re seeing when you open files in a text editor as you describe in your original post, and if you copied the text of those files and saved a new copy it’s very likely that it would not reproduce correctly.
yes, this method doesn’t lose any bits. one of its primary use before was email which was strictly text only.
Are those binary files by any chance?
I just mean like any file (pdf, jpeg, mp4, mp3, exe—
mp4/mp3 most famously for me
I find it so damn cool and incredible I can record something/anything right now and open the audio in a text file and its all right there—albeit in an incomprehensible format but there altogether.
Its like a thinking rock etching sound into stone
If you’re on Linux, you can convert that to something more human readable by piping it to base64. It works with any file, but I’ll use an image here:
cat image.webp | base64Which yields:
UklGRroEAABXRUJQVlA4WAoAAAAgAAAAYwAAQgAASUNDUKACAAAAAAKgbGNtcwRAAABtbnRyUkdC IFhZWiAH6AAIABoADgAJACBhY3NwQVBQTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA9tYAAQAA AADTLWxjbXMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA1k ZXNjAAABIAAAAEBjcHJ0AAABYAAAADZ3dHB0AAABmAAAABRjaGFkAAABrAAAACxyWFlaAAAB2AAA ABRiWFlaAAAB7AAAABRnWFlaAAACAAAAABRyVFJDAAACFAAAACBnVFJDAAACFAAAACBiVFJDAAAC FAAAACBjaHJtAAACNAAAACRkbW5kAAACWAAAACRkbWRkAAACfAAAACRtbHVjAAAAAAAAAAEAAAAM ZW5VUwAAACQAAAAcAEcASQBNAFAAIABiAHUAaQBsAHQALQBpAG4AIABzAFIARwBCbWx1YwAAAAAA AAABAAAADGVuVVMAAAAaAAAAHABQAHUAYgBsAGkAYwAgAEQAbwBtAGEAaQBuAABYWVogAAAAAAAA 9tYAAQAAAADTLXNmMzIAAAAAAAEMQgAABd7///MlAAAHkwAA/ZD///uh///9ogAAA9wAAMBuWFla IAAAAAAAAG+gAAA49QAAA5BYWVogAAAAAAAAJJ8AAA+EAAC2xFhZWiAAAAAAAABilwAAt4cAABjZ cGFyYQAAAAAAAwAAAAJmZgAA8qcAAA1ZAAAT0AAACltjaHJtAAAAAAADAAAAAKPXAABUfAAATM0A AJmaAAAmZwAAD1xtbHVjAAAAAAAAAAEAAAAMZW5VUwAAAAgAAAAcAEcASQBNAFBtbHVjAAAAAAAA AAEAAAAMZW5VUwAAAAgAAAAcAHMAUgBHAEJWUDgg9AEAALAQAJ0BKmQAQwA+8WSmTqmlKCYvmWqp MB4JZQDLnNaF2NMD2L3xQGb5nmLiGhGWxQuD8kwUSXF0u2UTgX0YrR3MY2SsRCNEQ8hZ6WkCUTih LdmsElHZVzoMwO/fj4X/ZSNT2R9qgxwqgEed891j4KCNRLK/tUbG3hZ3Mw2kixguSFIEcAgBtv8w eAu0PwAA/upMzBqq+dcN8viO7FpqpV6GvPcRILm+HsOQblnpHx03lASjGlSyGbkKUD3xA5KOqgq/ VEUJ4qF9VoAYFbFhQRAgkvmREk5umMj8sr9Np95+n/oP2Aq2VW5xU4F1xpD8Vd4Dp7Phwm9w/Dnf 94djRROFRYPZeg/1Q/qiROFRVRu2nBcgndbhc0x0h+kgvT/naeJOEqwNjYPlIiw/DGuxav7+x09R mf2mJto3ineDqfyMWUN83PmKqzGHkYGhZrTU478qjlQucDzWkwobnUmzhE6I+mDYkfiUVPcHyXbf xXRStyPiPZAkJZrE9OrjFNUeljRQdVTQqeBsy+O9VwDLU5GcKhBQHa4cj+/DGqUhi74WH0EuHsb3 EgZVNc1FbRm5QFOpjDSprGIRYxe6sFFDrDOg4DhWZRnOa7s68pGaDDpbqrORxzPHXPbs55/1HTas DDGzKFmTG4hJ2GUZKqjPcQ+MAAAACopy that into a text file and pass it to base64 with the decode flag, and you’ll get the original binary:
cat data.txt | base64 -d > data.binInspect it to see what kind of file it is:
file data.bin->data.bin: RIFF (little-endian) data, Web/P imageRename it so you can just double-click it to open it:
mv data.bin data.webpEnjoy the surprise.
You can also print files like that, scan them using OCR, and then restore them. A very inefficient way to do backups, but it works.
How is it representing it tho? Like does it have woven in there an array of hexcode colors for every microscopic pixel that makea up the picture.
Are images and audio files just arrays of frames which are arrays of pixels and sound units?
It just converts the raw binary data into character encoding, so it doesn’t matter what the source is (image, video, database file, etc). The source binary data is taken 6 bits at a time, then this group of 6 bits is mapped to one of 64 unique characters.
The decoding process is just the reverse of that: mapping the data back to binary form.
the answer to your how question is as needed.
some image and audio formats (especially older ones) are like that, yes. others use compression or other techniques to suit their need. like a sound can be a raw recording sample. or a sound can be described with Attack/Decay/Sustain/Release, along with octave and note etc. so a MIDI file is an audio file format without samples.
i once created an image format to be used for spiraling out images, instead of pixel arrays they were concentric circles of pixels that i could easily offset.
You can use a hex editor to view those files and even change them in some cases.
Something like this https://github.com/WerWolv/ImHex
