spleeter
open-unmix-pytorch
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spleeter | open-unmix-pytorch | |
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230 | 11 | |
24,878 | 1,157 | |
1.4% | 2.3% | |
1.5 | 0.0 | |
about 1 month ago | 7 days ago | |
Python | Python | |
MIT License | MIT License |
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spleeter
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Are stems a good way of making mashups
virtual dj and others stem separator is shrinked model of this https://github.com/deezer/spleeter you will get better results downloading original + their large model.
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Big News!
I have used multiple tools at this point. It depends on the scene. I use https://ultimatevocalremover.com/, https://github.com/deezer/spleeter/, iZotope RX. There are also multiple options online, I would personally recommend https://vocalremover.org/.
- Anybody here know what AI model does Steinberg's Spectralayers use to do stem separation?
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Show HN: Free AI-based music demixing in the browser
I tried to use it but I had some issues as others in the thread.
I have tried many sources and method over the years and settled on spleeter [0]. Works well even for 10+ minute songs, varying styles from flamenco to heavy metal.
[0] https://github.com/deezer/spleeter
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AI tools list sorted by category in one place
Spleeter is pretty good https://github.com/deezer/spleeter. Apparently it is used in some dj applications
- Software to lower tracks?
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Where does one legally get stems for remixes?
Haha GitHub and command lines and all can be confusing, but it’s certainly worth the effort because it lets you do everything for free.. here’s the online tutorial: https://github.com/deezer/spleeter/wiki/1.-Installation
- Audio and python help
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Are there any websites or programs that can separate vocals and drums from samples?
Chopped from their website Simple Stems is a quick and easy way to decompose any audio into it’s constituent parts. The plugin uses the well established Spleeter algorithm by Deezer to deconstruct songs into 2, 4 or 5 stems. The results are stunning, though more complicated mixes and live recordings are not always perfectly decomposed.
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Ask HN: Is there an ML model that can go from an audio song to sheet music?
I was going to post basic pitch from Spotify but it looks like billconan beat me to it. That said I can give you a bit more advice. The Spotify basic pitch model isn't too good at multi-track input. It's capable of it, but you may actually get better results if you separate out the tracks first and then run them individually through the basic pitch model.
In order to do this you can use a source/stem separation model like spleeter (https://github.com/deezer/spleeter) and then run the basic pitch model (or any other midi transcription model). There's other you can try which may yield better results, for example: (https://github.com/Music-and-Culture-Technology-Lab/omnizart)
Either way the key words you want to be looking for are "midi transcription" and "stem separation", should help you find more models to try for both steps. Good luck! :)
open-unmix-pytorch
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Show HN: Improved freemusicdemixer (AI music demixing in the browser)
In my first post, quite a lot of alternatives were discussed: https://news.ycombinator.com/item?id=36707877
The model I'm using is called Open-Unmix (https://github.com/sigsep/open-unmix-pytorch). In 2021, there was an update to Open-Unmix to include new weights, UMX-L, which made it perform better than it used to on the older weights (UMXHQ).
In the grand landscape of music demixing, I don't think UMX-L is near the top anymore.
_However_, the demixing performance of freemusicdemixer.com is very close to the full PyTorch performance of Open-Unmix UMX-L, despite the tricks I needed to get it working in the browser, such as splitting up the inference to operate on segments of the song, or making the LSTM operate on streaming segments rather than holding the entire track in the LSTM memory.
In my first release, I loaded and did inference on the entire track at once (like the PyTorch model), which frequently crashed or exceeded the 4GB WASM memory for medium or large-size tracks.
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Show HN: Free AI-based music demixing in the browser
* Post-processing step (bigger impact)
I tried to tackle the post-processing step in my C++ code (which would win ~1 dB in quality across all targets) but it's too tricky for now [2]. Maybe some other day.
1: https://github.com/sevagh/free-music-demixer/blob/main/examp...
2: https://github.com/sigsep/open-unmix-pytorch/blob/master/ope...
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Splitter.fm: Listen to the individual instrument/vocal tracks (known as "stems") for over 700 songs uploaded by 150+ artists
Or open-unmix. I've found it performs better than spleeter in some of my tests.
- I've created a website that extracts audio stems from songs using Spleeter, Demucs3, and Open Unmix for free.
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Cassiopeia: New Audio Splitter Superior to Spleeter and UMX
There's maybe something useful for you here?
https://github.com/facebookresearch/demucs
https://github.com/sigsep/open-unmix-pytorch
https://github.com/bytedance/music_source_separation
https://github.com/deezer/spleeter
- [N] Music Demixing (Audio Source Separation) Competition by Sony | ISMIR 2021
- [N Music Demixing (Audio Source Separation) Competition by Sony | ISMIR 2021
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[Research] Music Source Separation with AI networks: Comparison Tests incl. Spleeter, Lalal.ai, OpenUnmix and Extended Unmix
OpenUnmix ( is a neural network solution from Yuki Mitsufuji and Stefan Uhlich, music industry luminaries that work in Sony's core divisions.
What are some alternatives?
ultimatevocalremovergui - GUI for a Vocal Remover that uses Deep Neural Networks.
demucs - Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.
music_source_separation
SpleeterGui - Windows desktop front end for Spleeter - AI source separation
free-music-demixer - free website for client-side music demixing with Demucs + WebAssembly
SpleetGUI - Spleeter GUI version
ai-research-code
spleeter-web - Self-hostable web app for isolating the vocal, accompaniment, bass, and drums of any song. Supports Spleeter, D3Net, Demucs, Tasnet, X-UMX. Built with React and Django.
nodejs-poolController - An application to control pool equipment from various manufacturers.
1000sharks.xyz - AI "metal artist" with SampleRNN (mirror from GitLab)