Section: New Software and Platforms
UMX
open-unmix
Keywords: Source Separation - Audio
Scientific Description: Implements state of the art audio/music source separation with DNNs.
This software is intended to serve as a reference in the domain. It has notably been the object of several scientific communications: 1. An Overview of Lead and Accompaniment Separation in Music https://hal-lirmm.ccsd.cnrs.fr/lirmm-01766781/ 2. Music separation with DNNs: making it work (ISMIR 2018 Tutorial) https://sigsep.github.io/ismir2018_tutorial/index.html#/cover
Functional Description: This software implements audio source separation with deep learning, using pytorch and tensorflow frameworks.
It comprises the code for both training and testing the separation networks, in a flexible manner.
Pre and post-processing around the actual deep neural nets include sophisticated specific multichannel filtering operations.
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Authors: Antoine Liutkus, Fabian Robert Stoter and Emmanuel Vincent
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Publication: An Overview of Lead and Accompaniment Separation in Music