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StemKit is a free, open-source desktop app that separates songs into stems, lets you play along with the source video, and exports the resulting audio as WAV files. It can help musicians practise a part, study an arrangement, or make a karaoke-style mix. The project says processing happens on your computer, but using its YouTube workflow comes with an important terms-of-service caveat.

What StemKit does

StemKit’s project pages describe a workflow for finding a YouTube video or pasting its link, choosing which parts to separate, and listening in a player synchronized with the video. The available stem categories are vocals, drums, bass, other, guitar, and piano. The app also offers Karaoke and Acapella presets.

Once processing is complete, you can mute or solo stems, adjust their volume, click a waveform to seek, and play the parts together or separately. You can export one stem or all stems as WAV files. The project says those files can be imported into digital audio workstations such as Ableton, Logic, FL Studio, or GarageBand; no particular DAW is required.

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These are features described by the project, not independently measured results. The available project materials do not establish how accurately StemKit separates a specific song or instrument, so listen to the output before relying on it for practice, transcription, or a finished arrangement.

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How to use it to practise with a song

  1. Install StemKit and complete first-launch setup. The app may download its processing engine and other components before you can separate audio.
  2. Find a song. Use the built-in YouTube search or paste a video link, subject to the project’s warning about YouTube terms.
  3. Choose the parts you want. Select the available instruments or use a preset such as Karaoke or Acapella.
  4. Wait for separation to finish. StemKit describes parallel background processing with progress shown in the app.
  5. Listen and adjust. Use solo, mute, volume, waveform seeking, and synchronized playback to focus on the part you want to study.
  6. Export if needed. Save one or all stems as WAV to use elsewhere, including in a DAW.

The documented controls support listening and playing along, but the project pages do not establish a specific tempo-slowing feature. If slowing a part is essential to your practice, confirm that the version you install offers the playback control you need.

Supported computers and downloads

The README lists macOS 12 or later on Apple Silicon, Windows 10 or 11 on x64, and Linux x64 on Ubuntu 22.04 or an equivalent distribution. It lists CPU processing, NVIDIA GPU processing with CUDA, and AMD GPU processing on Linux through experimental ROCm support. Check the current project documentation for release-specific compatibility.

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StemKit’s README says the separation engine download is approximately 2 GB. The app bundles ffmpeg and says it can download a private Python runtime during first-launch setup if Python 3.9 or later is not detected; you do not need to install Python manually. Optional quality upgrades require additional downloads: the README lists a Mel-Band Roformer model at +913 MB and a fine-tuned Demucs model at approximately +320 MB. It also describes a two-shift refinement setting that may take up to three times longer. These are approximate setup figures from the project documentation, not performance benchmarks.

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Privacy: local processing, with an install-count ping

The project describes StemKit as running locally, without uploading videos, songs, the library, searches, or audio. Its README states, “Everything runs locally — no accounts, no API keys.” The same documentation discloses that the first app run sends a small POST request to a Cloudflare Worker to count installations. The listed payload includes a random install ID, app version, operating system, and architecture. The project says it does not build IP-address-based profiles or use cookies or identifiers tied to the user, and that an unsuccessful first attempt is retried on a later launch. The telemetry code is in the repository; the README says people building from source can remove the telemetry module or block the worker domain.

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YouTube use and licensing

The project README warns: “Downloading audio from YouTube violates their ToS for public products — keep this personal.” That is the project’s own warning, not a legal determination about every use or song. The available project materials do not establish whether you have permission to download, adapt, perform, or redistribute a particular track. Check the terms that apply to your use and the rights in the music before downloading or sharing audio.

The repository identifies StemKit as MIT licensed. That license applies to the project’s software; it does not grant rights to the music you process.

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Who StemKit suits

  • Useful if: you want a desktop workflow to isolate song parts, practise against synchronized playback, or export WAV stems for further work.
  • Consider the trade-offs: first launch involves a substantial download, processing depends on your computer, and the project does not publish an independent separation-quality benchmark.
  • Check before installing: confirm your operating system and processor match the listed support, and treat AMD ROCm support as experimental.

Project documentation: StemKit GitHub repository and StemKit website.

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