In this Chapter we covered:


  • What are the inputs/outputs of a source separation model

  • How mixtures are created

  • How data are used to train a source separation model (high level)

  • Why data are key for music source separation, and why they are hard to obtain


  • Overview of existing datasets

  • Important dataset characteristics to look out for

  • Why it’s important to always listen to your data!


  • Overview of the MUSDB18 dataset we will use in this tutorial

  • How to download the dataset preview clips using nussl

  • How to inspect our data via audition and visualization

Generating mixtures with Scaper

  • Why use Scaper rather than write ad-hoc mixing code

  • Overview of Scaper

  • How to prepare your source material (stems) for processing with Scaper

  • How to generate randomly augmented mixtures

  • The difference between incoherent and coherent mixtures and how to generate both

  • How to plug our Scaper mixing code into nussl