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MuseNet

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81–90 of 189 posts

Re: MuseNet

#81
I'm very into both music composition/production and ML, so this is neat. That being said, I think the "computer generated music" path is probably the wrong approach in the short term. Music is really complex and leans heavily on both emotions and creativity, which aren't even on the radar for AI. Being able to dynamically remix and modulate existing music is still really cool though.

I would kill for a VST tool that would take a set of midi tracks, and synthesize a new track for a specific instrument that "blends" with them. I would also kill for something that can take a set of "target notes" and break them up/syncopate/add rests to produce good melodies, or take a base melody and suggest changes to spice it up.

Re: MuseNet

#82

Earlier quoted context omitted.

It's probably only a matter of time before we have a GauGAN like interface for synthetic music creation...so you could say 'i want a sad song with a soft intro and a buildup of tension here with lyrics covering these emotions and things which lasts 7 minutes'. ML/DL is coming for a lot of the grunt work. It's coming for us as programmers as well. It's probably a few years away, but ML/DL

Given how easy it is to train a Transformer on any sequence data, and given how plentiful open source code is, I'd say "CodeNet" is probably less than a year away. OpenAI will probably do it first given they already have the setup.

I'm working on this.

I've been training on Stack Overflow and the model has already learned the syntaxes and common coding conventions of a bunch of different languages all on its own. Excited to see what else it's able to do as I keep experimenting.

Some sample outputs (you'll probably want to browse to some of the "Random" questions because by default it's showing "answers" right now and I haven't trained that model as long as some of the older question-generation ones): https://stackroboflow.com

Re: MuseNet

#83

While this may not be perfect composition, this is a surreal (and almost sad) moment in my life to hear music that is passable created by a computer under it's own volition. I work at a company that works with a lot of machine learning so I generally understand its limitations and haven't ever been an alarmist. That being said, I generally always thought of it being applied to automate work. For some reason I had alw…

Music created solely by machines will probably remain derivative and simplistic for a long time. I expect the biggest result of this research in the near term is that we'll be able to create tools that lower the skill and time required to create good music, kind of like an audio version of templates/autocomplete/spellcheck.

Re: MuseNet

#84

I think this is far, far beyond any algorithmic composition system ever made before. It displays an impressive understanding of the fundamentals of music theory. Most previous attempts at neural net composition restricted the training set to one style of music or even one composer, which is pretty silly if you understand how neural nets work. It was obvious to me if you used a very large network, chose the right inpu…

openai says they can do it:

Long-term structure MuseNet uses the recompute and optimized kernels of Sparse Transformer to train a 72-layer network with 24 attention heads—with full attention over a context of 4096 tokens. This long context may be one reason why it is able to remember long term structure in a piece

Re: MuseNet

#85
post #82

Earlier quoted context omitted.

Given how easy it is to train a Transformer on any sequence data, and given how plentiful open source code is, I'd say "CodeNet" is probably less than a year away. OpenAI will probably do it first given they already have the setup.

I'm working on this. I've been training on Stack Overflow and the model has already learned the syntaxes and common coding conventions of a bunch of different languages all on its own. Excited to see what else it's able to do as I keep experimenting. Some sample outputs (you'll probably want to browse to some of the "Random" questions because by default it's showing "answers" right now and I haven't trained that mode…

I've tried it as well and got good syntactic results. For more sensical programs, I think we will need more layers & attn heads. Perhaps someone will fork gpt-2 and add the sparse transformer to it.

Re: MuseNet

#87

This may be academically interesting, but the music still sounds fake enough to be unpleasant (i.e. there's no way I'd spend any time listening to this voluntarily).

Yes, the lack of human factor is very noticeable if you are a musician. I believe it's pretty similar to when grandmasters can tell if they are playing a human or a bot. Something that's hard to explain. Now saying if it's better or worse is just subjective.

Or where an AI can tell if they're playing a human or a bot.

Re: MuseNet

#89
post #71

While this may not be perfect composition, this is a surreal (and almost sad) moment in my life to hear music that is passable created by a computer under it's own volition. I work at a company that works with a lot of machine learning so I generally understand its limitations and haven't ever been an alarmist. That being said, I generally always thought of it being applied to automate work. For some reason I had alw…

Fear not, my friend, because the execution is only a part of why music and art as a whole carries meaning for us. Consider two tracks that are identical (forget copywrite for a minute). Between one that an AI generated and a human composed, I would personally grant the human-generated version more credit and enjoy it more. The story of how art is created and the stories of the artist are as substantial to appreciatin…

[deleted]

Re: MuseNet

#90
post #16
post #9

Neat output, the project is very similar compared to the Google Doodle a few weeks back, where they generated music based off of user-submitted notes. https://www.google.com/doodles/celebrating-johann-sebastian-... Since this is OpenAI, is MuseNet open source?

Not yet, but we plan to release the code & pre-trained model!

What kind of hardware (and what size data set) would you need to train with new types of music?

Doable with a single 1080ti and a couple of hundred midi files?

Also, can you do supervised learning with this - say melody input and chords (with good voice leading) output?

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