Audible convergence for optimal base melody extension with statistical genre-specific interval distance evaluation

Authors:
Ronald Hochreiter
Affiliations:
Department of Statistics and Decision Support Systems, University of Vienna, Vienna, Austria
Venue:
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
Year:
2006

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Abstract

In this paper, an evolutionary algorithm is used to calculate optimal extensions of a base melody line by statistical interval-distance minimization. Applying an evolutionary algorithm for solving such an optimization problem reveals the effect of audible convergence, when iterations of the optimization process, which represent sub-optimal melody lines, are combined to a musical piece. An example is provided to evaluate the algorithm, and to point out differences, when different musical genres, represented by different interval distance classification schemes, are applied.