From Genre Classification to Rhythm Similarity: Computational and Musicological Insights
From Genre Classification to Rhythm Similarity: Computational and Musicological Insights
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从流派分类到节奏相似性：计算和音乐学见解
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Eric J. Humphrey
中科院分区：
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作者：
T. Esparza;J. Bello;Eric J. Humphrey
传统上，音乐中节奏相似性的计算度量的开发和验证依赖于代理分类任务，通常将节奏相似性等同于流派。在本文中，我们进行了全面的，跨学科的探索的分类性能的国家的最先进的系统的节奏相似性。通过综合定量分析的方法与音乐学的角度来看，详细的洞察力获得到影响系统行为的各个方面，包括三个主要领域：一个给定的功能表示的节奏敏感性，用于评估的数据的特质，以及节奏相似性和流派之间的微妙关系。通过这项研究，我们提供了衡量计算系统的能力超越分类精度的角度，以及更深入地了解系统设计和评估方法作为一个音乐上有意义的练习。
Traditionally, the development and validation of computational measures of rhythmic similarity in music relies on proxy classification tasks, often equating rhythm similarity to genre. In this paper, we perform a comprehensive, cross-disciplinary exploration of the classification performance of a state-of-the-art system for rhythm similarity. By synthesizing the methods of quantitative analysis with a musicological perspective, detailed insight is gained into the various facets that affect system behaviour, consisting of three main areas: rhythmic sensitivities of a given feature representation, idiosyncrasies of the data used for evaluation, and the tenuous relationship between rhythmic similarity and genre. Through this study, we provide perspective on gauging the abilities of a computational system beyond classification accuracy, as well as a deeper understanding of system design and evaluation methodology as a musically meaningful exercise.