![]() Five-stem separation took around three minutes for 5.5 minutes of audio. On my five-year-old MacBook Pro using the CPU only, Spleeter processed audio at a rate of about 5.5x faster than real-time for the simplest two-stem separation, or about one minute of processing time for every 5.5 minutes of audio. ![]() It took a couple minutes to install the library, which includes installing Conda, and processing audio was much faster than expected. Five stems – Vocals, Drums, Bass, Piano, Other. ![]() Four stems – Vocals, Drums, Bass, Other.Two stems – Vocals and Other Accompaniment.The library ships with three pre-trained models: ![]() You can train it yourself if you have the resources, but the three models they released already far surpass any available free tool that I know of, and rival commercial plugins and services. Straight from command line, you can extract voice, piano, drums… from any music track! Uses and #Keras. The team at just released #Spleeter, a Python music source separation library with state-of-the-art pre-trained models! □✨
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