Binary Noises
Binary is the language of computers. Everything that you can put on a computer is represented in binary. From images to songs and much more. Binary is a base 2 counting system. Computers have 2 base values, powered and unpowered, so they can only count in base 2. Each digit in binary has a value of 2^(digit-1). The first digit when displaying 1 is worth 1. But the next digit is worth 2, so now we can make 3 by combining them like this: 11. This gets more complicated because as we add more digits the possible numbers multiply exponentially. so the third digit is worth 4, so now we can make 4: 100, 5: 101, 6: 110, and 7: 111. These numbers allow computers to store values as a series of on and off switches. But how do computers display characters? Each of the 255 characters typable on a keyboard is assigned to a value, pretty simple, but what about images. Images, at their simplest, are stored as numbers as well. long strands of numbers represent colored and uncolored pixels. 0,10,5,2 would display 0 white pixels followed by 10 black pixels, then 5 white and 2 black. It gets more complicated as we add more colors and tones, but that is the basic principle.
Audio:
But how do you represent audio? You can just store every possible sound and assign each one to a number, and even if you did it would take gigabytes to send 1 second of audio. But the trick is in the audio itself.
We hear sound waves. Everything our ears can process is represented by a wave that looks like this:
The wave moves up and down over time as the sound changes and evolves, using this graph which we can detect with microphones, we can plot points on the graph represented in binary like this:
The sampled sound wave doesn’t capture anything that happens between the points, so it loses finner details of the audio. Hertz represents the number of samples per second. Most audio is sampled from 44-48k hertz, meaning they plot that many points on the graph per second.
Sources and Images:
https://www.bbc.co.uk/bitesize/guides/zpfdwmn/revision/3