Sound synthesis is awesome!
Data is awesome, too. It presents the way we store our observations of the world we live in. Wavetable is a sound synthesis technique used to create periodic waveforms by using data.
Today, our portable machines are way more powerful than the first machines used for the wavetable synthesis, and they allow us to change the sound synthesis programs as they run. This activity is known as live coding and has been around for 20 years.
The workshop explores data-driven wavetable synthesis within a live coding context, and is a collaboration between Iván Paz and Julia Múgica, members of the lively Barcelona’s live coding community.
Join Iván and Julia at their sonification workshop where the data collected from natural processes will be translated into wavetables to make sound. The results will be used within a live coding context, so whether you’re interested in sound synthesis or live coding, this workshop is right up your alley!
About the mentors
Julia Múgica is a mexican scientist currently incurring in the artistic exploration of nature complex processes. With an interdisciplinary background that encompasses biology and computational physics, she is deeply interested in understanding how collectives make decisions that result in a behavioral synchrony. Recently, her curiosity extended to the artistic sphere, where the process of creation magnifies and prioritizes different aspects of the same phenomena. Her work includes animated particles design in processing language, noise design from random walks algorithms for modular synthesizers, and collaborations with the artist Lina Bautista in rhythm and collective patterns with interactive robots.
Iván Paz has backgrounds in physics, music and computer science. Iván’s work is framed in critical approaches to technology centered around from-scratch construction as an exploratory technique. Since 2010, he has been part of the live coding community and has presented workshops, conferences and concerts around America and Europe. He is currently working with machine learning techniques within live coding performance.