spleeter

We have hosted the application spleeter in order to run this application in our online workstations with Wine or directly.

Quick description about spleeter:

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

Features:

• Makes it easy to train music source separation models
• Vocals (singing voice) / accompaniment separation (2 stems) model
• Vocals / drums / bass / other separation (4 stems) model
• Vocals / drums / bass / piano / other separation (5 stems) model
• 2 stems and 4 stems models have state of the art performances on the musdb dataset
• It can be installed with Conda, with pip or be used with Docker

Programming Language: Python.
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