👉 Microphone math is the mathematical foundation behind converting sound waves into electrical signals that microphones can process. When sound waves hit a microphone, they cause the diaphragm to vibrate, which in turn alters the electrical charge of a coil attached to it within a magnetic field. This creates an alternating current (AC) signal proportional to the sound wave's amplitude and frequency. To make this signal usable, analog-to-digital converters (ADCs) sample the AC signal at regular intervals and quantize these samples into digital values, typically using a process called sampling theorem. The Nyquist-Shannon sampling theorem dictates that the sampling rate must be at least twice the highest frequency present in the sound to avoid aliasing. Once digitized, the signal is often processed using algorithms to enhance quality, reduce noise, or extract specific features. The final output can be compressed or encoded for storage or transmission, maintaining the integrity of the original sound while optimizing its representation.
