Vowel Formant Structure Predicts Metric Position in Hip-hop Lyrics

IF 1.3 2区 心理学 0 MUSIC
Paolo Ammirante, Fran Copelli
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引用次数: 4

Abstract

In order to be heard over the low-frequency energy of a loud orchestra, opera singers adjust their vocal tracts to increase high-frequency energy around 3,000 Hz (known as a “singer's formant”). In rap music, rhymes often coincide with the beat and thus may be masked by loud, low-frequency percussion events. How do emcees (i.e., rappers) avoid masking of on-beat rhymes? If emcees exploit formant structure, this may be reflected in the distribution of on- and off-beat vowels. To test this prediction, we used a sample of words from the MCFlow rap lyric corpus (Condit-Schultz, 2016). Frequency of occurrence of on- and off-beat words was compared. Each word contained one of eight vowel nuclei; population estimates of each vowel's first and second formant (F1 and F2) frequencies were obtained from an existing source. A bias was observed: vowels with higher F2, which are less likely to be masked by percussion, were favored for on-beat words. Words with lower F2 vowels, which may be masked, were more likely to deviate from the beat. Bias was most evident among rhyming words but persisted for nonrhyming words. These findings imply that emcees use formant structure to implicitly or explicitly target the intelligibility of salient lyric events.
元音形式结构预测嘻哈歌词中的度量位置
为了在嘈杂的管弦乐队的低频能量上被听到,歌剧歌手调整他们的声道,以增加3000赫兹左右的高频能量(被称为“歌手的共振峰”)。在说唱音乐中,韵律通常与节拍一致,因此可能会被响亮、低频的打击乐事件所掩盖。主持人(即说唱歌手)如何避免掩盖节拍押韵?如果emcees利用共振峰结构,这可能反映在节拍上和节拍外元音的分布上。为了验证这一预测,我们使用了MCFlow说唱歌词语料库中的单词样本(Condit Schultz,2016)。比较了节拍词和非节拍词的出现频率。每个单词包含八个元音核中的一个;每个元音的第一和第二共振峰(F1和F2)频率的总体估计是从现有来源获得的。观察到了一种偏差:F2较高的元音不太可能被打击乐掩盖,更倾向于节拍词。F2元音较低的单词(可能被掩盖)更有可能偏离节拍。偏倚在押韵词中最为明显,但在非押韵词则持续存在。这些发现表明,主持人使用共振峰结构来隐含或明确地针对显著歌词事件的可理解性。
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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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