A Computational Cognitive Model for the Analysis and Generation of Voice Leadings

IF 1.3 2区 心理学 0 MUSIC Music Perception Pub Date : 2020-02-01 DOI:10.1525/mp.2020.37.3.208
Peter M. C. Harrison,Marcus T. Pearce
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Abstract

Voice leading is a common task in Western music composition whose conventions are consistent with fundamental principles of auditory perception. Here we introduce a computational cognitive model of voice leading, intended both for analyzing voice-leading practices within encoded musical corpora and for generating new voice leadings for unseen chord sequences. This model is feature-based, quantifying the desirability of a given voice leading on the basis of different features derived from Huron’s (2001) perceptual account of voice leading. We use the model to analyze a corpus of 370 chorale harmonizations by J. S. Bach, and demonstrate the model’s application to the voicing of harmonic progressions in different musical genres. The model is implemented in a new R package, “voicer,” which we release alongside this paper.
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语音引导性分析与生成的计算认知模型
导声是西方音乐创作中常见的一项任务,其惯例与听觉感知的基本原则是一致的。在这里,我们介绍了一个语音引导的计算认知模型,旨在分析编码音乐语料库中的语音引导实践,并为未见过的和弦序列生成新的语音引导。该模型是基于特征的,根据Huron(2001)对语音引导的感知描述得出的不同特征,量化给定语音引导的可取性。我们使用该模型分析了巴赫的370首赞美诗和声语料库,并展示了该模型在不同音乐流派的和声进行发声中的应用。该模型是在一个新的R包“voicer”中实现的,我们将与本文一起发布。
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来源期刊
Music Perception
Music Perception Multiple-
CiteScore
3.70
自引率
4.30%
发文量
22
期刊介绍: Music Perception charts the ongoing scholarly discussion and study of musical phenomena. Publishing original empirical and theoretical papers, methodological articles and critical reviews from renowned scientists and musicians, Music Perception is a repository of insightful research. The broad range of disciplines covered in the journal includes: •Psychology •Psychophysics •Linguistics •Neurology •Neurophysiology •Artificial intelligence •Computer technology •Physical and architectural acoustics •Music theory
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