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A Simple Genetic Algorithm for Music Generation by means of Algorithmic Information Theory
 

Summary: A Simple Genetic Algorithm for Music Generation by means of
Algorithmic Information Theory
Manuel Alfonseca, Manuel Cebri´an and Alfonso Ortega
Abstract-- Recent large scale experiments have shown that
the Normalized Information Distance, an algorithmic informa-
tion measure, is among the best similarity metrics for melody
classification. This paper proposes the use of this distance as
a fitness function which may be used by genetic algorithms to
automatically generate music in a given pre-defined style. The
minimization of this distance of the generated music to a set of
musical guides makes it possible to obtain computer-generated
music which recalls the style of a certain human author. The
recombination operator plays an important role in this problem
and thus several variations are tested to fine tune the genetic
algorithm for this application. The superiority of the relative
pitch envelope over other music parameters, such as the lengths
of the notes, brought us to develop a simplified algorithm that
nevertheless obtains interesting results.
I. INTRODUCTION
The automatic generation of musical compositions is a

  

Source: Alfonseca, Manuel - Escuela Politécnica Superior, Universidad Autonoma de Madrid

 

Collections: Computer Technologies and Information Sciences; Engineering