MICROPLEX

MICROPLEX is a electro acoustic composition for percussion and realtime visualization. The work is based on a transcript of a talk[1] comparing micro biological structures, complex dense networks (such as the human brain and micro processors), and large scale human urban growth. As well as this essay/talk[2] concerning the same topic.

The work is in three movements that each have distinct sonic and visual environments associated with them. The first environment is of a 3d rendering of the Intel Montecito[3] chip that has been extruded in 3d space to create a urban landscape. This movement has four major sections corresponding to new sounds created by the drums as well as control of the environment and manipulations of the environment based on the incoming audio signal. The visuals of this environment then produce sound. All three movements are based around the idea of virtual 3d sculptures that produce sound.

still image from MICROPLEX mvt 1

The second movement is based on neural networks and playing the synoptic firings from a cascading model to create sound and visuals. The third movement represents a cell in it's natural environment dancing to the incoming audio. Using procedural animation, the central sphere is stretched and manipulated based on the incoming audio signal. All of this is done in real time.

Excerpts of this work have been shown at the 2015 Transplanted Roots: Percussion Symposium[4] in Montreal Canada, The 2015 Understanding Visual Music Conference[5] in Brasilia Brazil, Gray Area Arts[6] in San Francisco, and the Mckinney Avenue Contemporary[7] in Dallas Texas as a part of the 2015 Dallas Video Festival[8].

This work is being developed with the Mystic Talon Framework developed by Andrew Blanton. The framework allows from rapid prototyping and construction of audio visual works that both visualize sound as well as extract sound from visuals. The principal idea of the framework is to create feedback between multiple systems and insert the performer into the feedback loop to control it in real time. The work is based on previous work done in this area by groups such as NOISEFOLD[9], Semiconductor[10] and the Vasulka's[11] among others.