1000sharks.xyz
EfficientAT
| 1000sharks.xyz | EfficientAT | |
|---|---|---|
| 1 | 1 | |
| 0 | 183 | |
| - | - | |
| 10.0 | 6.7 | |
| over 1 year ago | 9 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...
EfficientAT
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Show HN: Free AI-based music demixing in the browser
Interesting, I attempted to do the same as you but stopped just shy of BPM matching.
However I did get sound similarity working using an audio tagging neural net [1]. I chopped off the first and last 15 seconds of every song in my collection and ran them all through this analysis which produces a ~520 dimensional vector. I then targeted specific endings I wanted to match and used Euclidian distance to find the closest matching song beginning.
YMMV but I thought it actually worked pretty well, I just never got to automating the BPM matching. I can try to look for my old script if you're interested :)
[1] https://github.com/fschmid56/EfficientAT
What are some alternatives?
open-unmix-pytorch - Open-Unmix - Music Source Separation for PyTorch
free-music-demixer - free website for client-side music demixing with Demucs + WebAssembly
umx.cpp - C++17 port of Open-Unmix-PyTorch with streaming LSTM inference, ggml, quantization, and Eigen
spleeter - Deezer source separation library including pretrained models.
demucs - Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.
pytorch-image-models - PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more