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 :https://deezer.io/releasing-spleeter-deezer-r-d-source-separation-engine-2b88985e797e 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 Subscribe ---Like --- Share Blog: http://technoprerak.blogspot.com Facebook: https://www.facebook.com/technodate Twitter: https://twitter.com/prerakm76 Instagram: https://www.instagram.com/technodate3/ Thanks for Watching :)