A hybrid approach to supervised machine learning for algorithmic melody composition

Rouven Bauer

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arXiv · 1612.09212

A hybrid approach to supervised machine learning for algorithmic melody composition

Rouven Bauer

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Abstract

In this work we present an algorithm for composing monophonic melodies similar in style to those of a given, phrase annotated, sample of melodies. For implementation, a hybrid approach incorporating parametric Markov models of higher order and a contour concept of phrases is used. This work is based on the master thesis of Thayabaran Kathiresan (2015). An online listening test conducted shows that enhancing a pure Markov model with musically relevant context, like count and planed melody contour, improves the result significantly.

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Rouven Bauer. 2016-12-29. A hybrid approach to supervised machine learning for algorithmic melody composition. https://arxiv.org/abs/1612.09212

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