"Generative art is an artwork partially or completely created by an autonomous system 🤖" - Music Generation with Magenta
Lets take our time machine and come back to the 18th century.
In 1792, a guy named Mozard created the Musikalisches Würfelspiel (musical dice) game.
The result of a dice roll determines which measure to add to the generated composition
The system is autonomous, because you don't decide the outcome
So basically the system is working for (with) you to reach a common goal: great music
But the result is as good as the system that creates it 😬.
Back in 2021, we're sitting on a pile of theorical knowledge about music, and lots of technology.
Brian Eno, who coined the term "generative music", who created numerous infinite albums
ORCA, one of many (esoteric) langages created for generative music.
Algorave, an underground music scene where the music is live-coded in front the audience (hence its name).
We have generative music tools to help us compose, produce, improvise, etc. 🚀
Claire Malrieux / Alexandre DuBreuil (skip to 11:00)
This generative artwork makes a relation between climate events (rain, tornados, etc.), the artist's drawings, and the music.
Generative text, generative voice, generative score (partition), generative audio, generative emotions!? 🤯
Some things are hard to do using traditional algorithm like text generation, voice generation, audio generation, etc. So we need a way of training a machine on human data...
With machine learning, you can use human data, and let the machine predict / generate based on what it has learned.
Claire Malrieux / Alexandre DuBreuil (skip to 10:50)
The machine tells us about its dream: "The street of the dream, interpretation too, I was very surprised that first I had..."
We go "full generative": generative dream text based on human dreams, analysing sentiments (sad, happy, etc.) of the text, generating speech, generating musical score...
Generating score based on style (rock, jazz, classical, etc.), emotion (sad, happy, etc.), instrument (drum, piano, etc.). With different neural networks (Recurrent Neural Networks, RNNs).
Generating audio is HARD, but we can generate sounds
based on cat meow!
Will neural networks take over the world?
No.
Remember: the generated music is only as good the generative system! And a generative system only reproduces what it knows.
Explore the role of deep learning in music generation and assisted music composition
Slides & More: alexandredubreuil.com/conferences