Audio Stem Separator with Demucs

Separates audio tracks into individual stems (vocals, drums, bass, other) using Meta’s Demucs neural network model via the demucs Python package. Supports batch processing of WAV and MP3 files, outputs isolated stems in FLAC or WAV format, and integrates with FFmpeg for format conversion and loudness matching post-separation.

Audio Stem Separator with Demucs

Separates audio tracks into individual stems (vocals, drums, bass, other) using Meta’s Demucs neural network model via the demucs Python package. Supports batch processing of WAV and MP3 files, outputs isolated stems in FLAC or WAV format, and integrates with FFmpeg for format conversion and loudness matching post-separation.

Installation

Method 1, Agent Skill Exchange

Method 2, Git clone

git clone https://github.com/agentskillexchange/skills.git && cd skills/skills/audio-stem-separator-demucs

Method 3, Download ZIP

  • Download the repository ZIP and extract skills/audio-stem-separator-demucs.

Method 4, Manual copy

  • Copy this skill folder into your local skills directory, then reload your agent tooling.

Method 5, Fork and sync

  • Fork the repository if you want to maintain local edits while syncing upstream changes.

Source