Audio Normalizer
Even out loudness across your audio to a consistent target level in one click. Free, no signup, works in your browser.
Everything runs inside your browser — your file is never uploaded to a server.
First run downloads the media engine (~30 MB) once, then it stays cached.
About this tool
Recordings from different sources rarely sound equally loud, forcing listeners to constantly reach for the volume knob. This normalizer analyzes your audio's loudness and applies gain adjustments so it hits a consistent target level, measured in LUFS, the standard broadcast and streaming loudness unit. It uses FFmpeg's loudnorm filter, which performs a two-pass analysis to correct both average loudness and peak levels without introducing clipping. Everything runs through WebAssembly directly in your browser, so no audio ever leaves your device. You can choose a target loudness suited for podcasts, music, or voice notes, preview the change, and export in your original format. It's especially useful when combining clips recorded on different microphones or at different times into one consistent-sounding file.
How to use this tool
1. Choose your audio file
Select the recording you want to normalize from your device.
2. Set the target loudness
Pick a LUFS target suited for your content type.
3. Run normalization
FFmpeg analyzes and adjusts loudness locally in two passes.
4. Download the result
Save the normalized audio file to your device.
Why use this tool
Inconsistent loudness is one of the most common complaints about home-produced audio, forcing listeners to adjust volume mid-playback. Normalizing to a standard LUFS target makes your podcast episodes, voiceovers, or music clips sound consistent with professionally mastered content, all without sending a single file to a server or waiting for a processing queue.
Tips & best practices
- Use around -16 LUFS for podcasts intended for streaming platforms and -14 LUFS for music.
- Normalize each clip before combining multiple recordings into one episode for a consistent listening experience.
- Check for clipping after normalizing very quiet recordings, since heavy gain boosts can occasionally reveal background noise.
Common use cases
- Matching loudness across multiple guest recordings in a podcast episode.
- Preparing a voiceover track to meet a video platform's loudness requirements.
- Leveling out music tracks compiled from different sources for a playlist.
- Making transcription audio consistently audible for speech-to-text accuracy.
- Balancing a WhatsApp voice note recorded too quietly before sharing.
Frequently asked questions
What loudness standard does normalization use?
It targets LUFS (Loudness Units Full Scale), the same measurement used by streaming and broadcast platforms.
Will normalizing introduce distortion?
No, the two-pass loudnorm filter adjusts gain while preventing clipping at the peaks.
Can I pick a specific target level?
Yes, you can set a target LUFS value suited to podcasts, music, or voice content.
Does it fix uneven volume within one recording?
It corrects overall loudness; for section-by-section spikes, trimming or compression works alongside it.
Why does my file need normalizing before combining with others?
Recordings from different microphones or settings vary in loudness, and normalizing brings them to a matching level.
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