How to Remove Background Noise From a Podcast Recording

There is a useful line running through every noise problem: is the noise
steady or not?

Steady noise — air conditioning, a fan, a computer, tape hiss, mains hum — has a
consistent fingerprint. Measure it during a quiet moment and you can subtract it from the whole
recording. This works well, and it is what noise removal actually is.

Everything else — a door, a dog, traffic, someone talking over you — is not
steady. There is no fingerprint to subtract. No filter of this kind removes it, and any tool
promising otherwise is selling you something.

Why fixed settings do not work

Every room is noisy at a different level. A denoiser set to expect noise at one level will
do almost nothing in a quieter room and destroy the audio in a louder one.

We measured this directly. With a fixed setting, the noise floor of our test file dropped
by one to two decibels — effectively nothing. Measuring the file’s actual noise floor
first and aiming the filter at that produced between 8 and 44 dB of reduction
depending on the strength chosen. Same filter, same file; the only difference was whether the
tool looked before it acted.

So the first question to ask any noise remover is: does it measure my file, or does it apply
the same setting to everything?

How much is too much

Here are real measurements from four strength settings on the same recording:

• Soft: 8.6 dB of noise removed
• Normal: 11.8 dB
• Aggressive: 22.1 dB
• Brutal: 43.5 dB

Across all four, the speech level moved by less than one decibel. That is the number to
watch: if a denoiser is making your voice quieter, it is removing the wrong
thing.

More is not automatically better. Very strong subtraction starts to thin out breaths and the
quiet ends of words, which is how audio gets that hollow, underwater quality. Start in the
middle, listen to a short preview, and only go further if you can hear that you need to.

The mistake worth avoiding: normalising afterwards

It seems obvious — clean the file, then bring it up to publishing loudness in the same
pass. We measured what that costs and it is worse than it looks.

Signal-to-noise improved by 11.1 dB with normalisation switched off, and only 2.2 dB with it
on. Normalising applies gain to everything left in the file, including whatever noise
survived, and its dynamic stage lifts the quiet passages hardest — which is exactly the
part you just cleaned.

The right order is two separate steps: remove the noise, then normalise the cleaned file
with a proper two-pass loudness tool. Same tools, same effort, dramatically better result.

Do not forget the low end

A high-pass filter around 80 Hz costs nothing and removes desk thumps, chair creaks,
handling noise and mains hum. Almost no speech content lives below 80 Hz, and that rumble
takes up headroom you would rather spend on the voice. Turn it on unless you have a specific
reason not to.

What about gating?

A gate silences anything below a threshold. Between sentences that sounds wonderfully clean;
at the end of words it chops the natural tail off consonants and breaths, and the result is
choppy in a way that is hard to unhear. Leave it off unless you have listened and decided you
want it.

Fix it at the source when you can

Every decibel you do not record is a decibel you never have to remove. Turn the air
conditioning off during takes. Move the microphone away from the laptop. Get closer to the
microphone so your voice sits further above the room. Five minutes of setup beats any amount
of processing.

When that is not possible — a remote guest with a noisy laptop, an archive recording,
a room you do not control — measure, remove, then normalise. In that order.