| dc.description.abstract | Algorithmic composition is a field that is close to 60 years old, and has seen
much research. Systems today are able to do a wide range of compositional
tasks, ranging from simple melody generation to fully automated orchestral
composition. Systems for computer aided composition are becoming
more and more common, either to evaluate music created by humans, or
as generators of raw material to be used by composers.
This Master s Thesis describes a novel implementation of a multi-objective
evolutionary algorithm, that is capable of generating short musical ideas
consisting of a melody and abstract harmonization. The implementation
is capable of creating these ideas based on provided material, or autonomously.
Three automated fitness features were adapted to the model to
evaluate the generated music during evolution, and a fourth was developed
for ensuring harmonic progression. Four rhythmical pattern matching features
were also developed.
The implementation produced 21 pieces of music, under various configurations,
that were evaluated in a study. The results of this study indicates
that the system is capable of composing ideas that are subjectively
interesting and pleasant, but not consistently. | |
