Loudness normalization conforms audio to a perceived loudness level. Learn why that's important in podcasting and how to make your podcast meet the standard.

Why a loudness normalization standard matters

Imagine you press play on a podcast episode. The intro music is a bit louder than the previous podcast you listened to, so you turn down the volume. Then, the main host comes in to introduce the topic, but they're quieter than the music, so you have to turn up the volume. Then, the cohost comes on and they're even quieter than the host, so you have to turn up the volume again or else not be able to hear them.

After a while, they segue into their interview with some bumper music, which is much louder than their voices, so you rush to turn down the volume before you damage your ears. This is a separately recorded interview and you are, again, having to continuously adjust the volume level so you can hear both participants and not damage your hearing.

At last, the podcast is over, but you have to turn down the volume one last time because the outro music is too loud. Then, the next podcast on your player starts playing, and it's too quiet, so you have to turn up the volume again, and the fight continues.

Does that sound familiar? That kind of frustration happens every day and could happen to any podcast—even the professionally produced ones!

That's why podcasts need loudness normalization! This would ensure the only time a listener must adjust their volume is when their environment changes, not when the podcast's audio changes.

This volume-fighting annoyance could be easily solved with loudness normalization in three places:

* Within each episode—ensuring the participants and sound clips are all at the same loudness level.

* Across episodes—ensuring that all episodes of one podcast are the same loudness as each other.

* Across podcasts—ensuring that podcasts from separate creators are all the same loudness.

Loudness normalization solves that by conforming all pieces of audio to the same standard.

How loudness is measured

Perceived loudness is now commonly indicated by “loudness units relative to full scale,” or “LUFS” (pronounced “luhfs”) for short. In the past, it was also called “loudness, K-weighted, relative to full scale” (LKFS), and there used to be some technical differences between LKFS and LUFS. But today, they're essentially the same—so much that whenever you see “LKFS” you can assume it also means “LUFS.”

LUFS are an absolute measurement relative to the full scale of 0 dB. Thus, you'll see LUFS indicated with negative numbers: -16 LUFS, -19 LUFS, -23 LUFS, and such. (You may also hear people abbreviate “negative 19” to “neg 19” in speech).

LUFS are an indication of the unit of measurement, which is actually “loudness units” (LU). LUs are equal units to decibels (dB). So if you need to amplify by 2 loudness units, you would simply amplify by 2 decibels.

The algorithm behind LUFS is designed to measure long-term averages of audio, not mere peaks (like most normalization tools). For example, audio with a loud but momentary peak will barely affect the long-term measured loudness of the processed section. But a standard normalizer would raise or lower the audio so that that peak reaches a target level, regardless of the rest of the audio.

Despite the louder portion in the beginning, this clip's loudness measurement would reflect the majority of the audio.

Loudness normalization is, therefore, the measurement of only the average, long-term perceived loudness of audio. It actually has nothing to do with dynamic range or peaks.

However, the user experience and perception of loudness is made of three parts:

* Loudness range (LRA): the statistical difference between loud and quiet over time, measured in loudness units (LU)

* Integrated/program loudness: the perceived loudness of selected audio, measured in LUFS