Neurorack Deep AI-based synthesizer constructed utilizing a Jetson Nano

Developers from the Artificial Creative Intelligence and Data Science (ACIDS) group, based mostly on the IRCAM Laboratory in Paris, France have created a novel Neurorack Deep AI-based synthesizer. Using an NVIDIA Jetson Nano mini PC the workforce created the challenge which mixes the ability of deep generative fashions with the compactness of a Eurorack machine. Check out the video under to be taught extra concerning the synthesizer challenge

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 musician 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 builders had a number of key design issues as they approached this challenge, together with:

• Musicality: the generative mannequin chosen can produce sounds which are unimaginable to synthesize with out utilizing samples.
• Controllability: the interface that they picked is helpful and straightforward to control.
• Real-time: the {hardware} behaves like a standard synthesizer and is equally reactive.
• Ability to standalone: it may be performed with out a pc.

Source : NVIDIA

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