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Quantitative Analysis of Phrasing Strategies in Expressive Performance: Computational Methods and Analysis of Performances of Unaccompanied Bach for Solo Violin

机译:表现力表达策略的定量分析:独奏小提琴无伴奏巴赫演奏的计算方法和性能分析

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摘要

This paper presents computational methods for quantitative description and analysis of expressive performance strategies in violin performances. We present general techniques for extracting beat-level tempo and loudness data, and the Local Maximum Phrase Detection (LMPD) method. The LMPD method equates local maxima in the loudness curve with interpreted phrases, and defines measures of phrase strength (clarity), phrase volatility (standard deviation), and phrase typicality (concurrence with norm), for characterizing each phrase. The methods are developed in the context of, and applied to, eleven recorded performances of the Andante movement from Bach's Sonata No. 2 in A minor BWV 1003 for solo violin by master violinists. For each performance, we present tempo and loudness summary statistics of the entire piece, its sections, and each phrase. In our experiments, we find that loudness is a more consistent indicator of phrasing strategies, suggesting that phrase structure may impose stricter constraints on dynamic than on tempo variation. The results of the LMPD method show that Kremer's performance exhibits the highest, and Enescu's the lowest, phrase volatility; Milstein's shows the highest average phrase typicality, and Enescu's the lowest; and, Grumiaux plays with the highest, and Menuhin the lowest, average phrase strength.
机译:本文提出了用于定量描述和分析小提琴演奏中表现策略的计算方法。我们介绍了提取节拍水平速度和响度数据的通用技术,以及本地最大短语检测(LMPD)方法。 LMPD方法将响度曲线中的局部最大值等同于已解释的短语,并定义了短语强度(清晰度),短语波动性(标准差)和短语典型性(符合规范)的度量,以表征每个短语。该方法是在大师级小提琴家针对独奏小提琴的A BWV 1003小调BWV 1003中从巴赫第二奏鸣曲中录制的十一首Andante乐章的演奏中开发并应用的。对于每次表演,我们都会呈现整首曲目,其各个部分和每个乐句的速度和响度摘要统计信息。在我们的实验中,我们发现响度是短语策略更一致的指标,表明短语结构可能对动态而不是对节奏变化施加更严格的约束。 LMPD方法的结果表明,Kremer的表现表现出最高的短语波动率,而Enescu的表现最低。 Milstein的平均短语典型性最高,Enescu的最低。并且,Grumiaux的平均乐句强度最高,而Menuhin的最低。

著录项

  • 来源
    《Journal of New Music Research》 |2008年第4期|325-338|共14页
  • 作者

    Eric Cheng; Elaine Chew;

  • 作者单位

    University of Southern California Viterbi School of Engineering, Los Angeles, California, USA;

    University of Southern California Viterbi School of Engineering, Los Angeles, California, USA|Radcliffe Institute for Advanced Study, Harvard University, Cambridge, Massachusetts, USA;

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  • 正文语种 eng
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  • 入库时间 2022-08-17 13:04:46

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