在过去的一个世纪里,从许多不同的角度分析了流行音乐的历史，与社会学家，音乐学家和哲学家都提供了不同的叙事特征的演变的流行音乐。然而,关于这一主题的定量研究仅在过去十年中开始，重点是从原始音频中提取的特征，这限制了音乐的低级成分的范围。本研究调查了流行音乐更抽象维度的演变，特别是旋律，使用1950年至2023年流行旋律的新数据集。要识别“旋律革命”，变化点检测被应用于多变量时间序列，包括与旋律的音调和节奏结构相关的特征。1975年和2000年的两次主要革命和1996年的一次较小革命，其特征是复杂性显着下降，被定位。革命将时间序列分为三个时代，用自回归分别建模，线性回归和向量自回归。自回归残差的线性回归强调了特征间的关系，在2000年后的旋律中变得更强。这些分析中出现的最重要的模式表明，随着时间的推移，流行旋律的复杂性降低，音符密度增加，尤其是2000年以来。
In the past century, the history of popular music has been analyzed from many different perspectives, with sociologists, musicologists and philosophers all offering distinct narratives characterizing the evolution of popular music. However, quantitative studies on this subject began only in the last decade and focused on features extracted from raw audio, which limits the scope to low-level components of music. The present study investigates the evolution of a more abstract dimension of popular music, specifically melody, using a new dataset of popular melodies spanning from 1950 to 2023. To identify \"melodic revolutions\", changepoint detection was applied to a multivariate time series comprising features related to the pitch and rhythmic structure of the melodies. Two major revolutions in 1975 and 2000 and one smaller revolution in 1996, characterized by significant decreases in complexity, were located. The revolutions divided the time series into three eras, which were modeled separately with autoregression, linear regression and vector autoregression. Linear regression of autoregression residuals underscored inter-feature relationships, which become stronger in post-2000 melodies. The overriding pattern emerging from these analyses shows decreasing complexity and increasing note density in popular melodies over time, especially since 2000.
