OpenViSTAI · Agents · Blockchain · Crypto
Menu
Audio & Voice AI

Spleeter

Spleeter is Deezer’s open-source Python library for separating mixed audio into musical stems with pretrained TensorFlow models.

Independent OpenViST project profile, based on linked sources.

Spleeter — OpenViST project profile in Audio & Voice AI.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Spleeter when you need programmatic or command-line separation of a mixed audio file into one of its documented stem arrangements.

Who it is for

  • Developers adding audio source separation to a Python pipeline
  • Audio users who want a command-line workflow for extracting vocals or instrument groups
  • Researchers or developers training separation models with datasets of isolated sources

Documented uses

  • Split a mix into vocals and accompaniment.
  • Extract vocals, drums, bass and other parts, or use a configuration that also separates piano.
  • Use separated audio files in a subsequent production, analysis or development workflow.
Before you choose

Requirements & limits

The source code is public under the MIT license. The README links to a Google Colab notebook for trying Spleeter without a local installation.

  • Spleeter offers three documented pretrained stem groupings, so choose based on which parts you need.
  • Local setup requires ffmpeg and libsndfile in addition to installing the Python package.
  • The project uses TensorFlow, and the README flags known Apple M1 compatibility issues.
  • Deezer distinguishes its library from third-party interfaces and services built on it, which it does not host or directly support.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Separate an example track into vocals and accompaniment

Install Spleeter and create two separated audio files from the documented example.

Before you start

  • Python environment with pip
  • ffmpeg and libsndfile
  • An audio file; the README provides an example MP3

Steps

  1. Install ffmpeg and libsndfile.

  2. Install Spleeter with pip.

  3. Download the documented example audio file.

  4. Run the documented spleeter separate -p spleeter:2stems -o output audio_example.mp3 command.

Expected outcome

The example produces vocals.wav and accompaniment.wav in the output/audio_example folder.

Guide limitations

  • The README no longer recommends Conda for installing Spleeter, although its example shows Conda for installing ffmpeg and libsndfile.
  • Known Apple M1 issues are associated mainly with TensorFlow compatibility; the README links to a workaround.
Evidence and transparency

Sources & review

Source record details
Source availability
Active
Sources checked
14 October 2026
Original website title
deezer/spleeter · Official homepage title · retained in its source language