open-unmix-pytorch
free-music-demixer
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open-unmix-pytorch | free-music-demixer | |
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11 | 7 | |
1,157 | 320 | |
2.3% | - | |
0.0 | 8.0 | |
11 days ago | 21 days ago | |
Python | Python | |
MIT License | MIT License |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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.
free-music-demixer
- Ask HN: What are some of the best user experiences with AI?
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Free-music-demixer adds multi-threading to run Demucs faster in the browser
Hi HN,
Over the Christmas break I added multi-threading to the WASM Demucs module in freemusicdemixer
Demucs (v4 hybrid transformer) is a much higher quality model than the previous default, but it ran very slowly when limited to one worker: ~17 minutes for an average 4-minute song
I have since implemented multi-threading with WebWorkers.
If you raise the "MAX MEMORY" setting to 16 GB or 32 GB, your track will demix within 7-5 minutes, producing state-of-the-art results.
There is also support for the Demucs 6-source model which adds piano and guitar stems.
Please reach out and be loud about any bugs or UX issues you encounter!: https://github.com/sevagh/free-music-demixer/issues
- Show HN: Improved freemusicdemixer – AI music demixing in the browser
- Show HN: Improved freemusicdemixer (AI music demixing in the browser)
- FLaNK Stack Weekly for 17 July 2023
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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...
What are some alternatives?
spleeter - Deezer source separation library including pretrained models.
danswer - Gen-AI Chat for Teams - Think ChatGPT if it had access to your team's unique knowledge.
demucs - Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.
heimdall - Dashboard for operating Flink jobs and deployments.
music_source_separation
dt - dt - duct tape for your unix pipes
ai-research-code
video2dataset - Easily create large video dataset from video urls
ultimatevocalremovergui - GUI for a Vocal Remover that uses Deep Neural Networks.
khoj - Your AI second brain. A copilot to get answers to your questions, whether they be from your own notes or from the internet. Use powerful, online (e.g gpt4) or private, local (e.g mistral) LLMs. Self-host locally or use our web app. Access from Obsidian, Emacs, Desktop app, Web or Whatsapp.
1000sharks.xyz - AI "metal artist" with SampleRNN (mirror from GitLab)
plate - The rich-text editor for React.