NEW !! Machine Learning model for separating VOCAL & Music

Dear Friends,

to help the research community in Music Information Retrieval (MIR) leverage the power of a state-of-the-art source separation algorithm. It comes in the form of a Python Library based on Tensorflow, with pretrained models for 2, 4 and 5 stems separation.

The problem of source separation has interested a large community of music signal researchers for a couple of decades now. It starts from a simple observation: music recordings are usually a mix of several individual instrument tracks (lead vocal, drums, bass, piano etc..). The task of music source separation is: given a mix can we recover these separate tracks (sometimes called stems)? This has many potential applications: think remixes, upmixing, active listening, educational purposes, but also pre-processing for other tasks such as transcription.

The actual separation can be achieved with a single command line, and it should work on your laptop regardless of your Operating System. For more advanced users, there is a python API class called Separator that you can manipulate directly into your usual pipeline.
Source :

Song Human
Artist The Killers
Album Absolute Music 59
Writers Elena Tonra, Igor Haefeli
Licensed to YouTube by
UMG (on behalf of Non-Wea/Other); UMPI, ASCAP, CMRRA,
LatinAutor - UMPG, UNIAO BRASILEIRA DE EDITORAS DE MUSICA - UBEM,
UMPG Publishing, PEDL, LatinAutor, and 12 music rights societies
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