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Years ago, I made a goofy experiment called Waxymash, taking four random isolated music tracks off YouTube, and colliding them into the world’s worst mashup. The team behind Open Unmix is also working on “ UMX PRO,” a more extensive model trained on a larger dataset, but it’s not publicly available for testing. The quality issues can likely be attributed to the model released with Open-Unmix, which was trained on a relatively small set of 150 songs available in the MUSDB18 dataset. Compare the output from Open-Unmix below for Lizzo’s isolated vocals, with drums clearly audible once they kick in at the 0:18 mark. In my testing, Open-Unmix separated audio at about 35% of the speed of Spleeter, didn’t support MP3 files, and generated noticeably worse results.

The release of Spleeter comes shortly after the release of Open-Unmix, another open-source separation library for Python that similarly uses deep neural networks with TensorFlow for source separation. You can compare the results generated by Spleeter to the famously viral isolated vocals by David Lee Roth, dry with no vocal effects applied. Spleeter had a difficult time with this one, but still not bad. 🎶 Van Halen – “Runnin’ With The Devil” Van Halen – “Runnin’ With The Devil” (Vocals Only) Van Halen – “Runnin’ With The Devil” (Music Only) I thought this one would be a disaster-the vocals are heavily processed and lower in the mix with a dynamic bass dominating the song-but it worked surprisingly well, though some of the snaps bleed through. 🎶 Billie Eilish – “Bad Guy” Billie Eilish (Vocals Only) Billie Eilish (Music Only) Compare this to 1:10 in the studio vocals. Some of the background vocals get included in both tracks here, which is probably great for karaoke, but may not be ideal for remixing. 🎶 Marvin Gaye – “I Heard It Through the Grapevine” Marvin Gaye (Vocals Only) Marvin Gaye (Music Only) No studio stems are available, but a fan used the Diplo remix to create this vocals-only track for comparison. Part of the beat makes it into Lil Nas X’s vocal track. 🎶 Lil Nas X w/Billy Ray Cyrus – “Old Town Road (Remix)” Lil Nas X (Vocals Only) Lil Nas X (Music Only) Spleeter gets a bit confused with the background vocals, with the secondary slide guitar bleeding into the vocal track. The original isolated vocals from the master tapes for comparison. 🎶 Led Zeppelin – “Whole Lotta Love” Led Zeppelin (Vocals Only) Led Zeppelin (Music Only) The piano is audible throughout PhonicMind’s track. 🎶 Lizzo – “Truth Hurts” Lizzo (Vocals Only) Lizzo (Music Only)Ĭompare the above to the isolated vocals generated by PhonicMind, a commercial service that uses machine learning to separate audio, starting at $3.99 per song. The 30-second samples are the separations from the simplest two-stem model, with links to the original studio tracks where available. I ran several songs through the two-stem filter, which is the fastest and most useful. Vocals sometimes get a robotic autotuned feel, but the amount of bleed is shockingly low relative to other solutions. Sample Resultsīut how are the results? I tried a handful of tracks across multiple genres, and all performed incredibly well.

When running on a GPU, the Deezer team report speeds 100x faster than real-time for four stems, converting 3.5 hours of music in less than 90 seconds on a single GeForce GTX 1080. Five-stem separation took around three minutes for 5.5 minutes of audio.

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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.

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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:

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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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