AI Audio Cleanup

Bad audio ends a piece of content faster than bad video ever does. Viewers forgive mediocre picture quality far more readily than they forgive audio they have to strain to understand. AI cleanup is now good enough to save a real recording made in imperfect conditions, but it has a ceiling, and pushing it past that ceiling replaces a noise problem with a worse and more obviously artificial one. The skill isn’t “run the cleanup,” it’s knowing where that ceiling is by ear.

Apply cleanup at a moderate setting first and listen before reaching for maximum strength. The instinct to max out the slider because “more is safer” is exactly backwards here, over-processing is its own distinct failure and it’s often worse than the noise you started with.

Listen specifically for the over-processing artifacts: a swishy or underwater quality, a voice that sounds thin or hollow, natural breath sounds disappearing entirely (which reads as unnatural even though technically “cleaner”). If you hear any of these, back the setting off, don’t push forward assuming the next notch fixes it.

Know what cleanup can’t fix. Severe clipping or distortion captured at the source, the audio equivalent of a blown-out overexposed image, is not repairable after the fact. Noise reduction reduces noise, it does not un-distort audio that was recorded too hot. If a clip has that problem, the actual fix is recording cleaner audio next time, not a heavier cleanup pass this time.

Always keep the unprocessed original file. Apply cleanup as a non-destructive pass, never overwrite the source, because you will occasionally need to go back and try a different setting once your ear catches something you missed the first time.