Audio Restoration: Spectral Gating & Hum Removal
Audio Cleaning involves analyzing the spectral frequency of a recording to mathematically subtract unwanted background noise, HVAC hiss, and electrical hum without destroying the primary vocal track.
Sending private interview recordings or sensitive voice memos to cloud AI processors is a major privacy risk. This tool utilizes the Web Audio API and Fast Fourier Transform (FFT) mathematics entirely client side.
Core Architecture & Mathematical Formula
Clean Audio = Raw Signal - Noise Profile (FFT Thresholding)
The algorithm analyzes a 'silent' portion of the audio to build a 'Noise Profile'. It then scans the entire file, acting as a microscopic volume knob (spectral gate) to turn down the specific frequencies that match the noise.
Best Practices & Essential Guidelines
- Always Record Room Tone: The algorithm needs to know what the 'noise' sounds like. Always record 10 seconds of absolute silence in your room before you start speaking. This provides the perfect Noise Profile for the cleaner.
- Target the 50/60Hz Hum: Electrical interference (like a bad microphone cable) creates a constant low frequency hum. Use a highly targeted notch filter exactly at 50Hz (Europe) or 60Hz (US) to surgically remove it.
- Don't Over Process: If you set the noise reduction threshold too high, the algorithm will start eating into the vocal frequencies, making the speaker sound robotic or like they are talking underwater (artifacting).