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Complex network structure of musical compositions: Algorithmic generation of appealing music

机译:音乐作品的复杂网络结构:吸引人的音乐的算法生成

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In this paper we construct networks for music and attempt to compose music artificially. Networks are constructed with nodes and edges corresponding to musical notes and their co-occurring connections We analyze classical Music from Bach. Mozart, Chopin, as well as other types of music such as Chinese pop music. We observe remarkably similar properties in all networks constructed from the selected compositions. We conjecture that preserving the universal network properties is a necessary step in artificial composition Of Music power-law exponents of node degree, node strength and/or edge weight distributions. mean degrees, Clustering coefficients, mean geodesic distances, etc. are reported. With the network constructed. music can be composed artificially using a controlled random walk algorithm, which begins with a randomly chosen note and selects the Subsequent notes according to a simple set of rules that compares the weights of the edges, weights of the nodes, and/or the degrees of nodes. By generating a large number of compositions, we find that this algorithm generates music which has the necessary qualities to be subjectively judged as appealing.
机译:在本文中,我们构建了音乐网络,并尝试人为创作音乐。网络是由与音符及其并发连接相对应的节点和边缘构成的。我们分析了巴赫的古典音乐。莫扎特,肖邦以及其他类型的音乐,例如中国流行音乐。我们观察到在所有由所选成分组成的网络中的特性都非常相似。我们推测,保留通用网络属性是节点度,节点强度和/或边缘权重分布的音乐幂律指数人工合成的必要步骤。报告平均度,聚类系数,平均测地距离等。随着网络的建设。音乐可以使用受控的随机游走算法人工合成,算法从随机选择的音符开始,然后根据一组简单的规则选择后续音符,这些规则比较边缘的权重,节点的权重和/或程度节点。通过生成大量乐曲,我们发现该算法生成的音乐具有主观判断为具有吸引力的必要质量。

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