mt3
spleeter
mt3 | spleeter | |
---|---|---|
10 | 230 | |
1,311 | 25,003 | |
2.1% | 0.9% | |
4.3 | 1.5 | |
8 months ago | about 2 months ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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mt3
- Ask HN: Is there an ML model that can go from an audio song to sheet music?
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Dj khaled plays guitar
Honestly, if I'm feeling a bit lazy, I'll use MT3 and clean things up with quantizing + by ear. If I'm transcribing a monophonic melody, I'll typically find the key by ear and use that to help guide my efforts. Of course, key changes and modulations do throw a wrench in things, but doing either is typically enough to get something roughed in for my purposes. I don't typically need to transcribe something for my own songs, as I'm comfortable enough with composing that I can work off of chord notation or random chord shapes and play with inversions and added tones to get something that I feel sounds nice.
- What is one way AI can improve music theory?
- Sony proposed DiffRoll, a diffusion-based automatic music transcription (AMT) model
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Flyway midi
its ai generated midi
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Atop a Cake transcribed by a neural network
I used the notebook in this github repository
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Macabre Plaza ai midi transcription
Direct MIDI transcription of Macabre Plaza using MT3.
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Spirit Train, Me, Blender, 2022
Here's the original MIDI if anyone is curious. I used MT3 to speed up the transcription process. That is what always takes the longest when doing a musical remake of any sort.
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I used ai to transcribe kkb to midi then sang over slowed+pitch shift (the model is called MT3 & its basically free karaoke/midi)
Link to model repo
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[R] MT3: Multi-Task Multitrack Music Transcription
github: https://github.com/magenta/mt3
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! :)
What are some alternatives?
omnizart - Omniscient Mozart, being able to transcribe everything in the music, including vocal, drum, chord, beat, instruments, and more.
ultimatevocalremovergui - GUI for a Vocal Remover that uses Deep Neural Networks.
open-unmix-pytorch - Open-Unmix - Music Source Separation for PyTorch
demucs - Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.
SpleeterGui - Windows desktop front end for Spleeter - AI source separation
SpleetGUI - Spleeter GUI version
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.
youtube-dl-gui - A cross-platform GUI for youtube-dl made in Electron and node.js
vstSpleeter - A VST interface to Spleeter
deemix-foobar2000 - Converts foobar2000 corrupted text list to Deezer album URL with Deezer API.
jukebox - Code for the paper "Jukebox: A Generative Model for Music"