Demucs

Demucs: The state-of-the-art AI model for music source separation, using a Hybrid Transformer architecture to isolate individual audio stems.

Demucs (Deep Extractor for Music Sources) is a powerful, open-source model developed by Meta AI (Facebook Research) for high-fidelity audio source separation. It operates directly on the raw waveform, bypassing traditional spectrogram-based methods to minimize artifacts. The latest version, Hybrid Transformer Demucs (HTDemucs), utilizes a dual-domain U-Net and cross-domain transformer to achieve a competitive 9.20 dB SDR on the MUSDB HQ test set, a benchmark for separating music into constituent tracks: vocals, drums, bass, and accompaniment. This makes it the go-to tool for musicians and researchers needing clean, fast extraction of stems for remixing or analysis.

https://github.com/adefossez/demucs