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Vocal Remover Beta

Separate vocals from the backing track using AI stem separation.

Worth knowing before you startThe separation model is around 40–80 MB depending on quality tier and downloads once on first use. Processing runs at roughly real-time speed or slower — a three-minute song takes two to four minutes. Separation quality is good on well-mixed commercial tracks but leaves artefacts on recordings with heavy reverb, close vocal-instrument mixing, or unusual instrumentation. Bleed between the stems (a little vocal in the instrumental, a little backing track in the vocal stem) is expected and varies by track.
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How to vocal remover

  1. Add a music track. The model downloads on first use — this is a one-time wait of around 30–60 seconds on a typical connection.
  2. Choose whether you want the instrumental, the vocal stem, or both.
  3. Wait for processing. A three-minute song takes two to four minutes. Download the result.

About this tool

Audio source separation — pulling individual instruments or vocals out of a mixed recording — was computationally intractable outside research labs until transformer-based models demonstrated that the problem was learnable. The models are still large, still slow, and still imperfect, but for the most common use case (separating a clear lead vocal from an instrumental backing) they produce results that are genuinely useful.

The separation artefacts are worth understanding before you start. The model works by predicting which frequency content belongs to the vocal mask and which belongs to the instrumental. On a well-produced track with clear spectral separation between voice and instruments, this works well. On a dense mix where the instruments occupy the same frequency range as the voice, the model has to make harder guesses and makes more mistakes. The "both stems" option lets you check both outputs and decide which is useful for your purpose.

Questions

Will the instrumental have any vocals in it?
Almost certainly some bleed, yes. No current client-side separation model achieves perfect separation on arbitrary music. The instrumental stem typically has ghost traces of the vocal, particularly on notes with significant reverb tail. How noticeable this is depends on the specific track — clean pop with prominent centre-panned vocals separates better than dense rock mixes.
Why does it take so long?
Audio source separation is a much heavier computation than most audio operations. The model processes overlapping windows of the audio through a deep network, and the inference runs in WebAssembly or WebGPU in your browser rather than a server with a GPU. We are being honest about the speed rather than pretending it is a fast operation.
Can I use the instrumental output as a karaoke backing track?
Yes, that is the primary use case. The quality of the output depends on how well the separation worked for the specific song. Expect it to be usable but not perfect — some vocals will be audible as faint artefacts in the backing.
What about separating other instruments?
The current model separates into two stems: vocals and everything else. Four-stem separation (vocals, bass, drums, other) requires a larger model that is impractical to run at this speed in a browser. We chose not to offer it until the quality and speed are acceptable rather than ship a slow, poor-quality version.