Monday, 2 May 2016

My first Algorave performance

So on Friday I performed at my first ever Algorave; an event where digital artists get together to perform music and create visual spectacles using computer code. The music is created using a form of composition called Live Coding where music is algorithmically programmed. I'd been interested in Live Coding ever since my Masters in Computer Music but found the area-specific language, such as SuperCollider and Tidal, a bit difficult to grasp and musical ideas slow to develop. This prompted me to start development on my own system, FoxDot.

FoxDot is a Python based language that takes an object-oriented approach to Live Coding and makes music by creating Player Objects that are given instructions such as the notes to play and their respective durations. The sounds themselves are synthesised in SuperCollider - for which FoxDot was originally designed as an abstraction.

The music at Algoraves comes in a variety of forms but mainly with the intention to make people dance. I was playing alongside some artists of whom I've watched countless videos and even written essays about, so I was very honoured to do so. I was very nervous as it was the first time I'd used my FoxDot language in a public setting and I think it showed in my performance. I noticed that many performers would stand (I chose to sit) and move rhythmically with the music and even spend some time away from the keyboard. By doing this I think  they not only could take a moment to enjoy the occasion, but also have a think about their next 'move' in terms of their sound. I was typing almost constantly and I think that  had a detrimental effect on the overall performance; the set was varied and had  too many lulls - but I did see some people dancing so I can't be completely disappointed.

Here's the whole event on YouTube (I start around 10 min)!

I'm next performing at the International Conference on Live Interfaces at the end of June at the University of Sussex and have given myself the challenge of including a computer vision aspect to the performance and I can't wait!