The evolution of inharmonicity and noisiness in contemporary popular music

TL;DR

This work investigates how inharmonicity and noisiness evolve in Contemporary Popular Music (CPM) from 1961 onward, using modified MPEG-7 features to separate contributions from noise and inter-partial inharmonicity. By defining HR-inharmonicity via $HR\text{-}inharmonicity = 1 - \text{HarmonicRatio}$, introducing Peak prominence as a robust noisiness metric, and applying PCA to obtain $PC1$ (total noise+inharmonicity) and $PC2$ (inharmonicity proportion), the authors reveal three diachronic phases in CPM and compare CPM with piano, orchestral, and musique concrète sources. They find CPM tends to be more inharmonic than other genres, with a mid-1980s peak and a later partial re-harmonization, while noisiness declines after 1986; weighting analyses by equal-loudness contours improves perceptual alignment and reduces outliers. The study links trends to production technologies (e.g., multi-tracking, distortion, samples) and discusses implications for pitch detection and transcription in CPM, highlighting that some studio-driven sounds may not map neatly to musical notes. Overall, the work provides a quantitative framework for understanding how studio practices shape timbral and harmonic structure in CPM and offers a data-driven basis for interpreting changes in popular music over time.

Abstract

Much of Western classical music relies on instruments based on acoustic resonance, which produce harmonic or quasi-harmonic sounds. In contrast, since the mid-twentieth century, popular music has increasingly been produced in recording studios, where it is not bound by the constraints of harmonic sounds. In this study, we use modified MPEG-7 features to explore and characterise the evolution of noise and inharmonicity in popular music since 1961. We place this evolution in the context of other broad categories of music, including Western classical piano music, orchestral music, and musique concrète. We introduce new features that distinguish between inharmonicity caused by noise and that resulting from interactions between discrete partials. Our analysis reveals that the history of popular music since 1961 can be divided into three phases. From 1961 to 1972, inharmonicity in popular music, initially only slightly higher than in orchestral music, increased significantly. Between 1972 and 1986, this rise in inharmonicity was accompanied by an increase in noise, but since 1986, both inharmonicity and noise have moderately decreased. In recent years (up to 2020), popular music has remained much more inharmonic than popular music from the 1960s or orchestral music involving acoustic resonance instruments. However, it has become less noisy, with noise levels comparable to those of orchestral music. We relate these trends to the evolution of music production techniques. In particular, the use of multi-tracking may explain the higher inharmonicity in popular music compared to orchestral music. We illustrate these trends with analyses of key artists and tracks.

Figures (19)

• Figure 1: Power spectrum for the first bass 'note' in Primaal's '<Fire!'. The vertical red and blue lines represent the fundamental and expected positions of the harmonics for the two highest spectral peaks.
• Figure 2: (a) power spectrum values for the BEA dataset. (b) relative loudness values.
• Figure 3: HR-inharmonicity for the four datasets. As in all the following similar figures, the lines represent median values, and the boxes represent interquartile ranges.
• Figure 4: Measures of peak prominence for the four datasets, compared with values for pink noise and white noise.
• Figure 5: Noisiness and HR-inharmonicity in the BEA dataset. In (a), the $x$-axis is noisiness, while the $y$-axis is HR-inharmonicity. Distributions are made closer to normal by skewing ($x_{norm} = x^{0.18}$ and $y_{norm} = y^{0.21}$) and normalising (subtraction of the median and division by the interquartile range). The gray lines indicate the median values for each axis. The blue line indicates the median inharmonicity value for a given noisiness value. The yellow line shows the axis that explains the most variance in the distribution. The red curve shows how the centroid for the music in the dataset from a particular year evolves over the period 1961--2022, smoothed for readability purposes. The amount of smoothing is similar to that of the 'smoothed' BEA curves in Figures \ref{['fig:harmonicratio1D']} and \ref{['fig:peakprominence1D']}. (b) shows the results of carrying out a PCA on the results shown in the graph on the left, with $x$-axis being PC1 and $y$-axis being PC2. The blue line indicates the median PC2 value for a given PC1 value, and the red curve shows how the centroid for a particular year evolves over the period 1961--2022.