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Neurorack Deep AI-based synthesizer built using a Jetson Nano

Developers from the Artificial Creative Intelligence and Data Science (ACIDS) group, based at the IRCAM Laboratory in Paris, France have created a unique Neurorack Deep AI-based synthesizer. Using an NVIDIA Jetson Nano mini PC the team created the project which combines the power of deep generative models with the compactness of a Eurorack machine. Check out the video below to learn more about the synthesizer project

AI-based Eurorack synthesizer

“The Neurorack is the first ever AI-based real-time synthesizer, which comes in many formats and more specifically in the Eurorack format. The current prototype relies on the Jetson Nano. The goal of this project is to design the next generation of music instrument, providing a new tool for musicians while enhancing the musician’s creativity. It proposes a novel approach to think and compose music. We deeply think that AI can be used to achieve this quest. The Eurorack hardware and software have been developed by our team, with equal contributions from Ninon Devis, Philippe Esling and Martin Vert.”

“Our original dream was to find a way to miniaturize deep models and allow them inside embedded audio hardware and synthesizers. As we are passionate about all forms of synthesizers, and especially Eurorack, we thought that it would make sense to go directly for this format as it was more fun! The Jetson Nano was our go-to choice right at the onset … It allowed us to rely on deep models without losing audio quality, while maintaining real-time constraints.”

The developers had several key design considerations as they approached this project, including:

  • Musicality: the generative model chosen can produce sounds that are impossible to synthesize without using samples.
  • Controllability: the interface that they picked is handy and easy to manipulate.
  • Real-time: the hardware behaves like a traditional synthesizer and is equally reactive.
  • Ability to standalone: ​​it can be played without a computer.

sources : NVIDIA

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