“Fibonacci Jungle” receives award at Generative Music Prize 2024, IRCAM

I have been awarded second place at the Generative Music Prize 2024, hosted by IRCAM in Paris on the 22nd of March for “Fibonacci Jungle”, a generative patch framework for Jungle and Drum & Bass based on the Fibonacci number sequence and implemented in Pure Data.

You can find the video presentation on concept and realization of the framework and more details on this year’s Generative Music Price winning submissions on the Forum IRCAM website.

The award presentation was part of the closing ceremony of the 30 years of Forum IRCAM workshop series which I was lucky to attend as well.

A heartfelt thank you for the appreciation to the whole jury and the team at IRCAM and congratulations to my fellow awardees Axel Chemla–Romeu-Santos and Simon Colton.

What is “Fibonacci Jungle”?

I’ve written and produced linear electronic dance music, more specifically Jungle and Drum & Bass, for several years. 

At some point I’ve realized that the majority of tracks in these genres is build up in pretty much the exact same way – intros, outros, breakdowns, drops etc. – and they all tend to have more or less the same length etc. 

It’s obviously not something new, that there are conventions in music composition. But the fact that the conventions in Jungle and Drum & Bass make tracks in these genres so predictable always left me a bit unsatisfied when going back into music writing. 

As an experiment, i’ve written a framework in Pure Data, that tries to challenge these conventions by replacing them with different structuring principles and add chance to a routine that usually demands to be in full control of how the music develops. 

That framework is titled “Fibonacci Jungle” because it’s based on the Fibonacci number sequence as structuring principle but it also uses genre specific settings and sounds. 

So it is a proposal to combine aesthetic consistency of Jungle music with a substantially different structural approach. 

A few months back, I’ve released different versions of various sample and parameter constellations using an earlier version of the framework.