Acosta Martínez Gerardo, Daffern Helena
AudioLab, School of Physics, Engineering and Technology, University of York, York, United Kingdom.
AudioLab, School of Physics, Engineering and Technology, University of York, York, United Kingdom.
J Voice. 2023 Dec 22. doi: 10.1016/j.jvoice.2023.11.020.
Vibrato is an oscillation in frequency, intensity, and timbre of the singing voice. Previous studies have found a relationship between its periodicity and perceived quality. The diversity of vibrato enriches the music and singer's performances but create challenges for quantifying and capturing the characteristics that contribute to achieving these expressive goals. Vibrato tones have been addressed using rate, extent, jitter, and shimmer; however, these do not necessarily capture relevant complex time-varying features. This paper applies techniques from disciplines that specialize in periodicity and complexity to provide insight into vibrato characteristics not yet understood.
This study aimed to assess whether nonlinear metrics are relevant features in characterizing and illustrating differences in vibrato behavior in opera and jazz singing, as well as considering the relationship of nonlinear metrics to other vibrato parameters.
Vibrato tones from published music material of world-class singers from opera and jazz were analyzed with entropy, recurrence, and the established parameters of rate, extent, jitter, and shimmer. Dimensionality reduction was employed to consider the relationship and significance of each of the metrics in collectively characterizing vibrato.
The principal component, explaining 40% of variability, had positive weights of determinism and line length derived from recurrence while having negative weights of rate, shimmer, and sample entropy. Using these components, the vibrato tones from opera compared to jazz singing were found to be more regular and had lower rate and extent, and it was possible to spotlight singers and notes with high periodicity.
Our study shows that nonlinear metrics applied to vibrato tones provide a valuable tool for observing and quantifying regularity in vibrato tones. The results of this study highlight the potential for more detailed descriptions of vibrato characteristics that may support categorization of individuals, genres, or musical expression in the future and could be applicable to pedagogical techniques.
颤音是歌声在音高、强度和音色上的一种振荡。以往的研究已经发现其周期性与感知质量之间存在关联。颤音的多样性丰富了音乐和歌手的表演，但也给量化和捕捉有助于实现这些表现力目标的特征带来了挑战。人们已经使用速率、幅度、抖动和闪烁等指标来研究颤音；然而，这些指标不一定能捕捉到相关的复杂时变特征。本文应用专门研究周期性和复杂性的学科技术，以深入了解尚未被理解的颤音特征。
本研究旨在评估非线性指标是否是刻画和说明歌剧演唱与爵士演唱中颤音行为差异的相关特征，并探讨非线性指标与其他颤音参数之间的关系。
利用熵、递归分析以及速率、幅度、抖动和闪烁等既定参数，对来自世界级歌剧和爵士歌手已发表音乐材料中的颤音进行分析。采用降维方法来考虑各个指标在共同刻画颤音时的关系和重要性。
解释了40%变异性的主成分，具有来自递归分析的确定性和线长的正权重，同时具有速率、闪烁和样本熵的负权重。利用这些成分，发现与爵士演唱相比，歌剧演唱中的颤音更规则，速率和幅度更低，并且能够突出具有高周期性的歌手和音符。
我们的研究表明，应用于颤音的非线性指标为观察和量化颤音的规律性提供了一个有价值的工具。本研究结果突出了更详细描述颤音特征的潜力，这可能在未来支持对个人、流派或音乐表达进行分类，并且可能适用于教学技术。
