## Abstract

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.

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.

Original language | English |
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Pages (from-to) | 712 - 716 |

Journal | Lecture Notes in Computer Science (LNCS) |

Volume | 3907 |

Publication status | Published - 1 Nov 2006 |