SplitSong

SplitSong

SplitSong is a web tool that separates a song into individual instrument and vocal tracks using AI. Upload an audio file or paste a YouTube link, and the service returns downloadable stems such as drums, bass, instrumental, and vocals.

The homepage demonstrates the workflow with a Michael Jackson Thriller example, showing separate download links for each stem type. Users need to sign in before uploading their own tracks.

SplitSong was created by Mark Doppler and focuses on a simple stem-splitting workflow for musicians, remixers, and creators who want isolated tracks without manual editing.

Top Features:
  1. Split uploaded songs into separate drum, bass, instrumental, and vocal tracks

  2. Import audio directly from a YouTube URL

  3. Download each generated stem as its own file

  4. Preview the full workflow with an on-page example track

  5. Sign in to process your own uploads

Pros:
  1. Simple interface focused on one job: stem separation

  2. Supports both file uploads and YouTube links

  3. Outputs clearly labeled drum, bass, instrumental, and vocal tracks

Cons:
  1. Homepage provides limited detail on pricing, limits, or supported file formats

  2. Sign-in appears required for personal uploads

  3. No visible advanced editing or mixing tools beyond stem export

FAQs:

What does SplitSong do?

SplitSong uses AI to separate a song into individual stems such as drums, bass, instrumental parts, and vocals.

Can I split a YouTube song?

Yes. The homepage lets you upload from YouTube instead of uploading a local audio file.

What stems does SplitSong generate?

The example output includes drums, instrumental, bass, and voice tracks as separate downloads.

Do I need an account?

The site includes sign-in and login options before uploading your own song.

Who built SplitSong?

SplitSong was created by Mark Doppler, linked from the homepage as @markdoppler on X.

Pricing:

Free

Tags:

Stem Splitter
Audio Separation
Vocal Remover
Music Production
YouTube Upload
Drums
Instrumental

Tech used:

Next.js
Tailwind CSS
Cloudflare
Google Analytics
Google Tag Manager

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