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Spleeter

Deezer source separation library — isolate vocals, drums, bass & more with AI

★ 28,255 GitHub MIT music-separationaudiosource-separationvocalstensorflowdocker Bild & Video

Überblick

Spleeter is an open-source source separation library developed by Deezer. It uses pretrained TensorFlow models to separate audio tracks into individual stems: vocals, drums, bass, piano, and other accompaniments. With 28k+ GitHub stars, it supports 2-stem, 4-stem, and 5-stem separation and can process audio 100x faster than real-time on GPU. Spleeter can be used via command line, Python API, or Docker, making it ideal for music producers, podcasters, researchers, and anyone needing AI-powered audio isolation.

Anforderungen

Min vCPU
2
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
4
Rec RAM
8192 MB
Rec Disk
20 GB

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Affiliate-Hinweis

Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  spleeter:
    image: researchdeezer/spleeter:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/spleeter:/data

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Anleitungen & Artikel

How to Separate Music Stems with Spleeter (Docker Quick Start)

Step-by-step guide to running Spleeter via Docker — isolate vocals, drums, bass, and other instruments from any audio file.

Jun 27, 2026

Spleeter: AI-Powered Music Source Separation by Deezer

Learn how Spleeter by Deezer uses TensorFlow to isolate vocals, drums, bass, and more from any audio track. Open source, MIT license, Docker-ready.

Jun 27, 2026