School of Music, Georgia State University, 75 Poplar Street, Atlanta, GA 30303, United States of America.
School of Music, Georgia State University, 75 Poplar Street, Atlanta, GA 30303, United States of America.
Cognition. 2023 Jan;230:105308. doi: 10.1016/j.cognition.2022.105308. Epub 2022 Oct 29.
Improvising musicians possess a stored library of musical patterns forming the basis for their improvisations. According to a prominent theoretical framework by Pressing (1988), this library includes linked auditory and motor information. Though examples of libraries of melodic patterns have been shown in extant recordings by some improvising musicians, the underlying motor component has not been experimentally investigated nor related to its auditory counterparts. Here we analyzed a large corpus of ∼100,000 notes from improvisations by one artist-level jazz pianist recorded during 11 live performances with audience. We compared the library identified from these recordings to a control corpus consisting of improvisations by 24 different advanced jazz pianists. In addition to pitch, our recordings included accurate micro-timing and key velocity (i.e., force) data. Following a previously validated procedure, this information was used to identify the underlying motor patterns through correlations between relative timing and velocity between notes in different iterations of the same pitch pattern. A computational model was, furthermore, used to estimate the information content and generated entropy exhibited by recurring pitch patterns with high and low timing and velocity correlations as perceived by a stylistically enculturated expert listener. Though both corpora contained a large number of recurring patterns, the single-player corpus showed stronger evidence that pitch patterns were linked to motor programs in that within-pattern timing and velocity correlations were significantly higher compared to the control corpus. Even when controlling for potentially greater baseline levels of motor self-consistency in the single-player corpus, this effect remained significant for velocity correlations. Amongst recurring 5-tone pitch patterns, those exhibiting more consistent motor schema also used less idiomatic pitch transitions that were both more unexpected and generated more uncertain expectations in enculturated experts than less consistently repeated patterns. Interestingly, we only found partial evidence for fixed pattern boundaries as predicted by the Pressing model and therefore suggest an expanded view in which the beginning and ends of idiomatic audio-motor patterns are not always clear-cut. Our results indicate that the library of melodic patterns may be idiosyncratic to the individual improviser and relies both on motor programming and predictive processing to promote stylistic distinctiveness.
即兴演奏者拥有一个存储的音乐模式库,这些模式构成了他们即兴创作的基础。根据 Pressing(1988)的一个著名理论框架,这个库包括了听觉和运动信息的链接。虽然一些即兴演奏者的现存录音中已经展示了旋律模式库的例子,但运动成分尚未经过实验研究,也没有与听觉对应物相关联。在这里,我们分析了一位艺术家级爵士钢琴家在 11 场现场表演中录制的约 100,000 个音符的大型语料库,这些表演都有观众在场。我们将从这些录音中识别出的库与由 24 位不同的高级爵士钢琴家即兴演奏的控制语料库进行了比较。除了音高之外,我们的录音还包括了精确的微节奏和键速度(即力)数据。根据一个经过验证的程序,通过在相同音高模式的不同迭代中音符之间的相对时间和速度之间的相关性,可以确定潜在的运动模式。此外,还使用计算模型来估计通过具有高和低时间和速度相关性的重复音高模式的信息内容和生成熵,这些模式是由具有风格化文化背景的专家听众感知的。尽管两个语料库都包含大量重复出现的模式,但单播放器语料库显示出更强的证据表明音高模式与运动程序相关联,因为与控制语料库相比,模式内的时间和速度相关性明显更高。即使在控制单播放器语料库中潜在更高的运动自我一致性水平的情况下,这种效应对于速度相关性仍然是显著的。在重复的 5 音高模式中,那些表现出更一致的运动图式的模式也使用了更少的惯用音高转换,这些转换对于具有文化背景的专家来说比不那么一致重复的模式更出乎意料,产生的不确定性期望也更高。有趣的是,我们只发现了部分证据支持 Pressing 模型所预测的固定模式边界,因此建议采用一种扩展的观点,即惯用的音频运动模式的开始和结束并不总是清晰明确的。我们的结果表明,旋律模式库可能是个体即兴演奏者特有的,既依赖于运动编程,也依赖于预测处理,以促进风格的独特性。