Spleeter: AI has learned how to effectively separate audio recordings into music and vocals


Spleeter is the Deezer source separation library with pretrained models written in Python and uses Tensorflow. It makes it easy to train source separation model (assuming you have a dataset of isolated sources), and provides already trained state of the art model for performing various flavour of separation :

  • Vocals (singing voice) / accompaniment separation (2 stems)
  • Vocals / drums / bass / other separation (4 stems)
  • Vocals / drums / bass / piano / other separation (5 stems)

2 stems and 4 stems models have state of the art performances on the musdb dataset. Spleeter is also very fast as it can perform separation of audio files to 4 stems 100x faster than real-time when run on a GPU.

We designed Spleeter so you can use it straight from command line as well as directly in your own development pipeline as a Python library. It can be installed with Conda, with pip or be used with Docker.

https://github.com/deezer/spleeter

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