acidsound / stemroller

Isolate vocals, drums, bass, and other instrumental stems from any song

Home Page:https://www.stemroller.com

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Wondering when your feature request or issue will be addressed? Please see the StemRoller Roadmap. Also, join our Discord server so we can communicate with you more directly.

StemRoller

StemRoller is the first free app which enables you to separate vocal and instrumental stems from any song with a single click! StemRoller uses Facebook's state-of-the-art Demucs algorithm for demixing songs and integrates search results from YouTube.

Simply type the name/artist of any song into the search bar and click the Split button that appears in the results! You'll need to wait several minutes for splitting to complete. Once stems have been extracted, you'll see an Open button next to the song - click that to access your stems!

Quick Start

Using StemRoller couldn't be easier - just head to the StemRoller website or the releases page and download the latest version! That bundle includes everything you need to split stems. If, however, you want to get involved in StemRoller development, read on...

Install Dependencies

git clone https://github.com/stemrollerapp/stemroller.git
cd stemroller
npm i -D

Windows/macOS

npm run download-third-party-apps

Linux (Experimental)

Install ffmpeg globally using your preferred package manager, and install demucs globally with pip.

Run in Development Mode

npm run dev

Run in Production Mode (Linux)

Linux is not yet officially supported, but thanks to some kind contributors, we now have experimental Linux support if you're willing to run StemRoller from source. You can, of course, also run in development mode on Linux.

npm run build:svelte && npm run start

Production Build

Windows

npm run build:win

macOS

npm run build:mac

License

Your choice of Public Domain (Unlicense) or MIT No Attribution - please read the LICENSE file for more information.

About

Isolate vocals, drums, bass, and other instrumental stems from any song

https://www.stemroller.com

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Language:Svelte 84.8%Language:JavaScript 14.5%Language:CSS 0.5%Language:HTML 0.1%