New music system reveals spectral contribution to statistical learning
New music system reveals spectral contribution to statistical learning
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DOI：
10.1016/j.cognition.2022.105071
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发表时间：
2022-02-25
期刊：
影响因子：
3.4
通讯作者：
Loui，Psyche
中科院分区：
文献类型：
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作者：
Loui，Psyche
语音和音乐的知识依赖于感知声音之间关系的能力，以便形成对统计结构的稳定的心理表征。虽然有证据表明从声音事件的统计特性中学习音阶结构，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，我们证明了谱内容是获得音阶结构的重要线索。在两个实验中，参与者在半小时之前和之后用预先定义的统计结构在一种新的音乐音阶中对旋律进行了探查音调评级。在实验1中，参与者被随机分配到没有暴露的控制组，或者暴露在听到纯音或复合音序列的暴露组中。在实验2中，参与者被随机分配到暴露组，他们听到由奇数和偶数谐波构成的复杂音调。通过将暴露前/暴露后的评级与暴露期间内音调的统计结构相关联来评估学习结果。光谱信息显著影响对统计结构的敏感性：参与者在接触所有测试音色后能够学习，但在学习与音阶结构一致的奇数谐波音色时表现最好。结果表明，频谱幅度分布是统计学习的有用线索，提示音阶结构可能是通过暴露于声音的频谱分布而获得的。
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.