Categorization of Musical Patterns by Self-Organizing Neuronlike Networks
Categorization of Musical Patterns by Self-Organizing Neuronlike Networks
复制标题
通过自组织神经元网络对音乐模式进行分类
DOI：
10.2307/40285472
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发表时间：
1990
期刊：
影响因子：
2.3
通讯作者：
Robert O. Gjerdingen
中科院分区：
文献类型：
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作者：
Robert O. Gjerdingen
自组织类神经网络的模拟被用来演示未经训练的听众如何能够将他们对数十种不同音乐特征的感知整理成稳定、有意义的图式。首先介绍了此类网络的显着特征，特别是 Stephen Grossberg 提出的自适应共振理论（ART）网络。然后讨论了四级 ART 网络的计算机模拟（称为 L'ART pour l'art 的模拟）如何对莫扎特最早的六首作品中的音乐事件进行独立分类。该网络能够从这些作品中提取重要的语音主导组合（实际上还可以检测新莫扎特版本中可能存在的错误），这表明这种方法有望研究普通听众如何处理音乐的多维复杂性。此外，网络产生的分类暗示了音乐层次结构的替代概念。在一个规矩的家庭里，整洁是最重要的美德。碗碟排列在橱柜里，就像阅兵式上的士兵一样。书籍在书架上排列整齐。一切都有一个地方，一切都在它的位置上。参观者感触
Simulations of self-organizing neuronlike networks are used to demonstrate how untrained listeners might be able to sort their perceptions of dozens of diverse musical features into stable, meaningful schemata. A presentation is first made of the salient characteristics of such networks, especially the adaptive-resonance-theory (ART) networks proposed by Stephen Grossberg. Then a discussion follows of how a computer simulation of a four-level ART network - a simulation dubbed L'ART pour l'art - independently categorized musical events in Mozart's six earliest compositions. The ability of the network to abstract significant voiceleading combinations from these pieces (and in fact to detect a possible error in the New Mozart Edition) suggests that this approach holds promise for the study of how ordinary listeners process music's multidimensional complexity. In addition, the categorizations produced by the network are suggestive of alternative conceptualizations of music's hierarchical structure. a prim household, tidiness is a paramount virtue. Dishes line cupboards like soldiers on parade. Books march across shelves in close-order drill. There is a place for everything, and everything is in its place. A visitor senses