Compute the gain needed to reach a specific loudness target and confirm that true peaks stay within headroom.
Podcast listeners expect consistent volume across episodes. Sudden jumps in level force them to adjust their device volume, distracting from the conversation. Streaming platforms often normalize to around −16 LUFS for stereo content. Delivering audio near that target preserves dynamics while preventing distribution services from applying aggressive gain changes that could distort your master.
LUFS (Loudness Units relative to Full Scale) captures perceived loudness using ITU-R BS.1770 weighting and gating. dBFS measures peak or sample amplitude relative to the digital ceiling. Normalization balances both metrics: we adjust overall gain according to LUFS and check that resulting peaks stay below a safety margin, typically −1 dBFS. The gain factor converts the difference between target and current loudness into a decibel change.
The table below illustrates common normalization scenarios for a −16 LUFS target.
| Current LUFS | Gain dB | Linear factor |
|---|---|---|
| −20 | +4 | 1.58 |
| −18 | +2 | 1.26 |
| −16 | 0 | 1.00 |
| −14 | −2 | 0.79 |
| −12 | −4 | 0.63 |
Keep this conversion handy when adjusting clips manually or setting the makeup gain on a loudness processor.
Normalization alone does not control dynamic range. If your show swings from whisper-quiet dialogue to booming music, consider gentle compression before normalization. The compressor relationship (with input level , threshold , ratio ) guides how dynamics reduce. After processing, re-run the calculator to ensure peaks stay below −1 dBFS and that intelligibility remains intact.
Different services use different loudness targets. YouTube favors −14 LUFS, while broadcast outlets may require −23 LUFS and limit true peaks to −2 dBFS. Adjust the target field to preview gain for each platform. If you create multiple masters, document the results with the copy feature so your team can reproduce settings consistently.
This calculator assumes accurate LUFS and true peak measurements from your meter. It does not analyze audio files or apply gain automatically. Pair it with batch processors such as ffmpeg or loudness-capable DAWs to normalize an entire season. For accessibility, combine normalization with transcript creation and chapter markers so every listener enjoys a polished experience.