Check your podcast episode against the -16 LUFS / -1 dBTP standard — instant pass/fail on loudness and true peak.
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This checks your level — it doesn't change it.
Failing the check? Fix the level with the free Volume Normalizer. Need other platform targets or the full 6-point QA? Use the LUFS Meter or Voice Quality Analyzer.
Upload an episode to check it against the −16 LUFS podcast standard
Podcasts are delivered at -16 LUFS integrated with a true peak ceiling of -1 dBTP. LUFS (Loudness Units relative to Full Scale) measures how loud the whole episode actually sounds to a listener, weighted the way human ears hear — not the instantaneous electrical level a plain dB meter shows. -16 LUFS is the level Apple Podcasts and Spotify target for spoken-word stereo shows, and it is the standard this checker measures every upload against.
Spoken-word content has to stay intelligible in noisy places — cars, trains, kitchens, earbuds on a run. -16 LUFS sits a little hotter than the -23 LUFS broadcast standard and the -14 LUFS most music streaming uses, which keeps dialogue clear without forcing listeners to ride the volume knob. Land within ±1 LU of -16 and your episode will sit comfortably next to other shows.
A sample peak meter reads the level of the digital samples; true peak (dBTP) estimates the higher level the analog waveform actually reaches between those samples. Lossy encoders like MP3 and AAC can push those inter-sample peaks past 0 dBFS and clip on playback even when the file never looks clipped. Leaving 1 dB of headroom (-1 dBTP) prevents that distortion after encoding, which is why platforms set the ceiling there.
Apple Podcasts and Spotify don't play your file at whatever level you exported — they normalize it toward their house loudness on the way to the listener. An episode louder than -16 LUFS is turned down (you keep the distortion but lose the loudness); a much quieter one may be turned up. Deliver on target and you stay in control of how your show sounds after normalization.
Most spoken-word podcasts are effectively mono — one or two people talking, no stereo image to preserve — so many producers publish mono files to roughly halve the file size at the same quality. The -16 LUFS target is identical either way: loudness is measured on the program, not the channel count. This checker reports the integrated loudness of whatever you upload, mono or stereo.
-16 LUFS integrated, with a true peak at or below -1 dBTP — the level Apple Podcasts and Spotify target for stereo spoken-word shows. Aim to land within ±1 LU of -16. Upload your episode above and this checker tells you the exact loudness you're at and whether it passes.
True peak (dBTP) estimates the highest level the analog waveform reaches between digital samples. MP3 and AAC encoding can overshoot those inter-sample peaks and clip on playback even when the file never touches 0 dBFS, so the podcast standard caps true peak at -1 dBTP — a single decibel of headroom that keeps the encode clean.
Streaming platforms normalize every episode toward a house loudness level, so a show delivered far from -16 LUFS gets turned up or down to match. If yours sounds quiet next to other podcasts, its integrated loudness is probably well below -16 LUFS, or its loudness range is so wide that the quiet passages dominate. Measure the integrated LUFS here — that's the number platforms normalize against — and bring it to -16 before publishing.
Either works. Most spoken-word shows are effectively mono, and publishing a mono file roughly halves the size at the same quality. The -16 LUFS target doesn't change with the channel count — loudness is measured on the whole program — so a mono export and a stereo export of the same episode pass or fail the same way.
If it's too quiet, raise the level; too loud, bring it down; in both cases use a true-peak limiter set to -1 dBTP so the encode stays clean. The free Volume Normalizer does all of that in one click — set it to -16 LUFS, run your file, then re-check it here to confirm the pass.
VoiceDeck adds AI-powered audio & video review and delivery for your whole team — so every file ships in spec, automatically.
