Northeastern University, USA.
Cognition. 2022 Jul;224:105071. doi: 10.1016/j.cognition.2022.105071. Epub 2022 Feb 25.
Knowledge of speech and music depends upon the ability to perceive relationships between sounds in order to form a stable mental representation of statistical structure. Although evidence exists for the learning of musical scale structure from the statistical properties of sound events, little research has been able to observe how specific acoustic features contribute to statistical learning independent of the effects of long-term exposure. Here, using a new musical system, we show that spectral content is an important cue for acquiring musical scale structure. In two experiments, participants completed probe-tone ratings before and after a half-hour period of exposure to melodies in a novel musical scale with a predefined statistical structure. In Experiment 1, participants were randomly assigned to either a no-exposure control group, or to exposure groups who heard pure tone or complex tone sequences. In Experiment 2, participants were randomly assigned to exposure groups who heard complex tones constructed with odd harmonics or even harmonics. Learning outcome was assessed by correlating pre/post-exposure ratings and the statistical structure of tones within the exposure period. Spectral information significantly affected sensitivity to statistical structure: participants were able to learn after exposure to all tested timbres, but did best at learning with timbres with odd harmonics, which were congruent with scale structure. Results show that spectral amplitude distribution is a useful cue for statistical learning, and suggest that musical scale structure might be acquired through exposure to spectral distribution in sounds.
关于言语和音乐的知识依赖于对声音之间关系的感知能力,以便形成统计结构的稳定心理表示。尽管存在从声音事件的统计属性学习音乐音阶结构的证据,但很少有研究能够观察到特定的声学特征如何独立于长期暴露的影响而对统计学习做出贡献。在这里,我们使用一种新的音乐系统表明,频谱内容是获取音乐音阶结构的重要线索。在两项实验中,参与者在接触具有预定统计结构的新音乐音阶的半小时内,在旋律前和后完成探针音评分。在实验 1 中,参与者被随机分配到无暴露对照组或纯音或复音序列暴露组。在实验 2 中,参与者被随机分配到听到用奇数谐波或偶数谐波构建的复音的暴露组。通过将暴露前后的评分与暴露期间的音高的统计结构相关联来评估学习结果。频谱信息显著影响对统计结构的敏感性:参与者可以在暴露于所有测试音色后进行学习,但在使用与音阶结构一致的奇数谐波音色进行学习时效果最佳。结果表明,频谱幅度分布是统计学习的有用线索,并表明音乐音阶结构可能通过暴露于声音中的频谱分布来获得。