Spleeter: a Fast and Efficient Music Source Separation Tool with Pre-Trained Models

Romain Hennequin 1 min read

We present and release a new tool for music source separation with pre-trained models called Spleeter. It was designed with ease of use, separation performance and speed in mind. It is based on Tensorflow and makes it possible to:

  • separate audio files into 2, 4 or 5 stems with a single command line using pre-trained models.
  • train source separation models or fine-tune pre-trained ones with Tensorflow (provided you have a dataset of isolated sources).
spleeter_logo

The performance of the pre-trained models are very close to the published state of the art and is, to the authors knowledge, the best performing 4 stems separation model on the common musdb18 benchmark to be publicly released. Spleeter is also very fast as it can separate a mix audio file into 4 stems 100 times faster than real-time on a single GPU using the pre-trained 4-stems model.

We have released a longer blog post about Spleeter and there has been nice reviews in the press. Notably on TheVerge.com (EN), Gigazine.net (JP) and RollingStone.fr (FR)