Audible Convergence for Optimal Base Melody Extension with Statistical Genre-Specific Interval Distance Evaluation

In this paper, an evolutionary algorithm is used to calculate optimal
extensions of a base melody line by statistical interval-distance minimiza-
tion. Applying an evolutionary algorithm for solving such an optimiza-
tion problem reveals the e®ect 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 di®erences of the ¯nal score, when di®er-
ent musical genres, represented by di®erent interval distance classi¯cation
schemes, are applied.