1000sharks.xyz
open-unmix-pytorch
| 1000sharks.xyz | open-unmix-pytorch | |
|---|---|---|
| 1 | 11 | |
| 0 | 1,160 | |
| - | 1.5% | |
| 10.0 | 5.6 | |
| over 1 year ago | 4 days ago | |
| HTML | Python | |
| MIT License | MIT License |
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1000sharks.xyz
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Show HN: Free AI-based music demixing in the browser
OK, so, tangentially related: I tried to do something once - I took small chunks of songs generated by SampleRNN in an attempt to stitch together the ones that sounded the most similar.
The script [1] uses Essentia Chromaprint [2] to "grade" the similarity of audio tracks, and combine the ones with the closest chromaprint.
I have a track on Soundcloud which uses the above technique (mashing together short generated clips by their chromagram), trained on Cannibal Corpse [3]
1: https://github.com/sevagh/1000sharks.xyz/blob/master/sampler...
2: https://essentia.upf.edu/reference/std_Chromaprinter.html
3: https://soundcloud.com/user-167126026/1000sharks-domainal-sk...
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?
EfficientAT - This repository aims at providing efficient CNNs for Audio Tagging. We provide AudioSet pre-trained models ready for downstream training and extraction of audio embeddings.
spleeter - Deezer source separation library including pretrained models.
umx.cpp - C++17 port of Open-Unmix-PyTorch with streaming LSTM inference, ggml, quantization, and Eigen
demucs - Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.
music_source_separation
free-music-demixer - free website for client-side music demixing with Demucs + WebAssembly
ai-research-code
ultimatevocalremovergui - GUI for a Vocal Remover that uses Deep Neural Networks.
flask-website-template