MAKING ELECTRONIC MUSIC WITH EXPERT MUSICAL AGENTS Angel´ Faraldo, Carthach´ O´ Nuanain,´ Daniel Gomez,´ Perfecto Herrera, Sergi Jorda` Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain
[email protected] ABSTRACT system is packed with a real time control where for a sin- gle loop the ”commonness” within a style, the density and This demo describes a collection of intelligent musical the syncopation values can be modified. These three con- agents that act and react to real-time manipulation. We re- trollers add much plasticity and reversibility to the trans- port on a number of probabilistic approaches that address formation of a single loop so a loop can be easily explored the generation of rhythm, harmony and texture idioms that and modified to fit specific aspects of a live performance exist in electronic music today. The presentation combines or an offline composition. these individual components into a virtual orchestra that The second system, GenDrum, takes a different ap- can play synchronously in time. proach, applying a Genetic Algorithm to iteratively evolve new patterns based on a fitness function that determines the 1. INTRODUCTION rhythmic similarity of the evolved patterns to an initial tar- get pattern. At present two distance measures are provided, Electronic dance music (EDM) is a category of popu- the Hamming distance and the directed-swap distance. The lar music that encompasses styles such as techno, house, Hamming distance simply counts the number of onsets that trance, and dubstep, and utilises electronic instruments differs while the more complex direct-swap attempts to such as synthesizers, drum machines, sequencers, and capture the horizontal displacement more acutely by using samplers.