A reflexive audio environment using genetic algorithms

Sonification – the production of sound to represent some form of data or information, has been applied in various fields including analysis of financial, meteorological and physiological data. A system overview is presented which is based on analysis of socio-spatial behaviour via video capture of a given environment. The example given is a busy commuter environment such as a train station. Activity in the environment is mapped to a set of musical performance parameters, and also forms the basis for controlling an optimisation function based on genetic algorithms (GA). The aim is to develop a socially reflexive audio environment, where those present unconsciously interact with the input, and output, of the sonification process. The output of the system is a series of musical chords, optimised as regards their musical ‘fitness’ as defined by three consonance criteria.