My excitement for this new knowledge changed the capacities and goals of my artistic practice. Even though the learning curve was steep and quite difficult, to begin with, I found myself exploring new ideas about code manipulation that allowed me to increase control with acoustic and electronic environments. I became able to design code that could react and sound in specific ways, in order to better blend with the extended techniques used by the acoustic instruments that I worked with in this project.
This was an encouraging process! It gave me a strong insight into my future research proposals. It inspired me to think about machine-performer co-creation, and the potential of AI for community engagement, sound aesthetic development, and performative interactiveness, while engaging in scientific knowledge and sonification as main materialities.
When I wrote my research proposal, my coding skills were on a very basic level, so naturally, diving into a research project involving so much work in this area was risky, but at the same time exciting! So I asked myself:
I decided to trust my experience and professional skills in composition and performance, so I proposed Sounding Numbers. One of my goals was to develop structural and creative programming tools in the context of my artistic practice. I believed that going through this process in a research context, could guide me to new aesthetic parameters and potentialities within programmed sound designs. The process could also help me find a more defined way of blending acoustic and electronic instruments within my artwork.
Planning was a key point for success. Therefore, for the four semesters that I had ahead, I carefully planned how to explore different coding languages with increasing difficulty, and apply that knowledge to my regular artistic practice toward an artistic outcome.
In the first and third semesters of my project, I attended the IT University in Copenhagen, where I studied object-oriented programming and data mining. They were challenging studies to take at a master's level, as the lectures were meant for people with a background in computer science. During these studies, I programmed a computer game and made data science analysis by applying unsupervised algorithms and neural networks for clustering and prediction.
do I need to be proficient in all the areas of my research to be able to create a sustainable process and a professional artistic outcome?
I learned how to code in JAVA, Python, and SuperCollider, and worked with Raspberry Pi, ESP32 boards, motion and CO2 sensors, heart rate monitors, and midi controllers. I also applied machine learning algorithms to my last sonification. In the piece, I AM THE OCEAN, the sounding outcome changes based on predictive values triggered by the environment.
In an overall sense, I think that researching new and unknown materialities, in the frame of artistic practice-based research, can create a strong setting for novel discoveries by opening a potential for knowledge and spiritual artistic development.
