Research and Development

The problem of creating generative music systems has been approached in different ways, each guided by different goals, aesthetics, and biases. These generative systems can be divided into two broad categories: the first is an ad hoc definition of the generative algorithms, the second is based on the idea of modeling and generalizing from preexistent music for the subsequent generation of new pieces. Most inductive models developed in the past have been probabilistic, while the majority of the deductive approaches have been rule based.

I approach the problem of inductive modeling of high level musical structures from a dynamical systems and signal processing perspective, focusing on motion per se independently of particular musical systems or styles. The point of departure is the construction of a state space that represents geometrically the dynamics of a given piece of music. I address ways in which this state space can be modeled deterministically, as well as ways in which it can be transformed to generate new musical structures.

This was my masters thesis.

Some sound examples.