Rock Music: Granular and Stochastic Synthesis based on the Matanuska Glacier

Moving from social media to environmental data, today I discuss Mara Helmuth’s Rock Music, a sonification of the melting of an Alaskan glacier.

Mara Helmuth uses data from sediment granulation in a lake formed by the melting of the Matanuska glacier in Alaska during a 24-hour period. Time, grain size and grain frequency were measured and mapped onto parameters for waveform, additive, granular and physical modelling synthesis.

Matanuska_Glacier_From_The_Air
The Matanuska Glacier seen from the air
Mapping

By mirroring the diurnal cycle of d10 grain frequencies (the frequency of the smallest 10% of grains), Helmuth created a waveform period which produced a complex set of partials for drones.
Sediment grain frequency data was mapped to partial frequency and grain size to duration. In a further phase, Helmuth mapped sediment grain size to partial frequency and grain frequency to amplitude which resulted in slowly changing events.
For granular synthesis, Helmuth mapped sediment grain frequency to grain rate and grain size to grain frequency. Another approach was mapping sediment grain frequency to grain frequency and grain size to grain duration. Finally, Stochgran (a granular synthesis application developed by Helmuth) to generate events of grain distribution where the frequency value was derived from sediment grain sizes and rates were derived from sediment grain frequencies and variations on this method.
Helmuth used the STK Synthesis Toolkit to create stochastic sounds like multiple-attack shaker instruments such as maracas. Grain frequency was mapped to the number of objects, grain size to energy, with all the 22 instruments playing at a randomly varied time about 10 times per second. The gradual ascents and descents in energy and density result in a pulsing texture.
On a macro level, grain parameters were mapped to event density on the two dimensions. The increasing frequency of grain events is mapped to more additive synthesis layer and higher grain rates near the end of the Matanuska Etude. There are also more stochastic sounds present near the end of the piece.

You can find an excerpt of Matanuska Etude below, and read a paper which explains the project in-depth here.

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