Free AI-based music demixing in the browser
Hi all, I've spent some time working on music demixing or music source separation algorithms, which take in a mixed song and output estimates of isolated components (e.g. vocals, drums, bass, other). I took a popular PyTorch model with good performance (Open-Unmix, UMX-L weights), reimplemented the inference steps in C++, and compiled it to WebAssembly for a free client-side music demixer.
Free AI-based music demixing in the browser launched on July 13, 2023 with 190 votes, #202 of 4,347 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 3 years on.
In plain words
This is a free browser-based tool that separates music into individual components such as vocals, drums, bass, and other instruments. It uses Open-Unmix, a popular AI model for music source separation, reimplemented in C++ and compiled to WebAssembly for client-side processing. Users can upload mixed songs and receive isolated audio tracks, with all processing happening in their browser rather than on external servers.
written from the facts on this page · September 2026
Does a similar job
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Hi HN, Last time I showed free-music-demixer, which people seemed to enjoy. It was a static website with a Javascript + WASM module to perform music demixing (or music source separation) using an AI model UMX-L (Open-Unmix) running client-side in the browser. Since then, I have overhauled the project and made several improvements: - The demixing/separation quality is higher now, since I implemented the missing post-processing step - Memory usage is lower now by performing a custom segmented inference with a streaming LSTM, which should allow larger tracks (or, dare I say,…
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