ffmpeg-normalize 1.39.0

Normalize audio via ffmpeg

ffmpeg-normalize

A utility for batch-normalizing audio using ffmpeg.

This program normalizes media files to a certain loudness level using the EBU R128 loudness normalization procedure. It can also perform RMS-based normalization (where the mean is lifted or attenuated), or peak normalization to a certain target level.

✨ Features

• EBU R128 loudness normalization — Two-pass by default, with an option for one-pass dynamic normalization
• RMS-based normalization — Adjust audio to a specific RMS level
• Peak normalization — Adjust audio to a specific peak level
• Selective audio stream normalization — Normalize specific audio streams or only default streams
• Video file support — Process video files while preserving video streams
• Docker support — Run via Docker container
• Python API — Use programmatically in your Python projects
• Shell completions — Available for bash, zsh, and fish
• Album Batch normalization – Process files jointly, preserving relative loudness

🚀 Quick Start

1. Install a recent version of ffmpeg and Python 3.10 or higher
2. Run pip3 install ffmpeg-normalize and ffmpeg-normalize /path/to/your/file.mp4, alternatively install uv and run uvx ffmpeg-normalize /path/to/your/file.mp4
3. Done! 🎧 (the normalized file will be called normalized/file.mkv)

🆕 What's New

• Version 1.39.0 preserves the input bit depth by default when encoding to formats like FLAC, so 16-bit input stays 16-bit without needing -e "-sample_fmt s16". Use --no-keep-bit-depth to opt out. It also adds --keep-mtime to copy the input file's modification time to the output, which is useful for preserving when a track was added to a music library.

  Example:

  ffmpeg-normalize input.flac -nt peak -t 0 -c:a flac --keep-mtime -o output.flac
  

• Version 1.38.0 writes the normalized output directly to the destination without using temporary files

• Version 1.36.0 introduces presets with --preset! Save and reuse your favorite normalization configurations for different use cases. Comes with three built-in presets: podcast (AES standard), music (RMS-based batch normalization), and streaming-video (video content). Create custom presets too!

  Example:

  ffmpeg-normalize input.mp3 --preset podcast
  

  applies the podcast preset (EBU R128, -16 LUFS) to your file. Learn more in the presets guide.

• Version 1.35.0 has batch/album normalization with --batch. It preserves relative loudness between files! Perfect for music albums where you want to shift all tracks by the same amount.

  Example:

  ffmpeg-normalize album/*.flac --batch -nt rms -t -20
  

  shifts the entire album so the average RMS is -20 dB, preserving the original relative loudness as mastered.

• Version 1.34.0 brings selective audio stream normalization! You can now:

  • Normalize specific audio streams with -as/--audio-streams (e.g., -as 1,2 to normalize only streams 1 and 2)

  • Normalize only default audio streams with --audio-default-only (useful for files with multiple language tracks)

  • Keep other streams unchanged with --keep-other-audio (copy non-selected streams without normalization)

    Example:

    ffmpeg-normalize input.mkv -as 1 --keep-other-audio
    

    normalizes stream 1 and copies all other audio streams unchanged.

Other recent additions:

• Shell completions (v1.31.0) — Tab completion for bash, zsh, and fish shells. See the installation guide for setup instructions.
• --lower-only option — Prevent audio from increasing in loudness, only lower it if needed (works with all normalization types).

See the full changelog for all updates.

📓 Documentation

Check out our documentation for more info!

🤝 Contributors

The only reason this project exists in its current form is because @benjaoming's initial PRs. Thanks for everyone's support!

Benjamin Balder Bach 💻	Eleni Lixourioti 💻	thenewguy 💻	Anthony Violo 💻	Eric Jacobs 💻	kostalski 💻	Justin Pearson 💻
ad90xa0-aa 💻	Mathijs 💻	Marc Püls 💻	Michael V. Battista 💻	WyattBlue 💻	Jan-Frederik Schmidt 💻	mjhalwa 💻
07416 📖	sian1468 ⚠️	Panayiotis Savva 💻	HighMans 💻	kanjieater 🤔	Ahmet Sait 💻	georgev93 💻
David Bern 💻	randompersona1 💻
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