Generating structured music using quality metrics based on Markov models

In this research, a first order Markov model is built from a corpus of bagana music, a traditional lyre from Ethiopia. Different ways in which low order Markov models can be used to build quality assessment metrics for an optimization algorithm are explained. These are then implemented in a variable neighbourhood search algorithm that generates bagana music. The results are examined and thorougly evaluated. Due to the size of many datasets it is often only possible to get rich and reliable statistics for low order models, yet these do not handle structure very well and their output is often very repetitive. A method is proposed that allows the enforcement of structure and repetition within music, thus handling long term coherence with a first order model.