The Changing Sound of Music: An Exploratory Corpus Study of Vocal Trends Over Time

Recent advancements in audio processing provide a new opportunity to study musical trends using quantitative methods. While past work has investigated trends in music over time, there has been no large-scale study on the evolution of vocal lines. In this work, we conduct an exploratory study of 145,912 vocal tracks of popular songs spanning 55 years, from 1955 to 2010. We use source separation to extract the vocal stem and fundamental frequency (f0) estimation to analyze pitch tracks. Additionally, we extract pitch characteristics including mean pitch, total variation, and pitch class entropy of each song. We conduct statistical analysis of vocal pitch across years and genres, and report significant trends in our metrics over time, as well as significant differences in trends between genres. Our study demonstrates the utility of this method for studying vocals, contributes to the understanding of vocal trends, and showcases the potential of quantitative approaches in musicology.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-10
DOI
https://doi.org/10.5281/zenodo.14877316
Primary Topic
Nanoporous metals and alloys
Type
article
Field-Weighted Citation Impact
0.00
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article

The Changing Sound of Music: An Exploratory Corpus Study of Vocal Trends Over Time

Zenodo (CERN European Organization for Nuclear Research)
Nanoporous metals and alloys
article

The Changing Sound of Music: An Exploratory Corpus Study of Vocal Trends Over Time

article en

Abstract

Recent advancements in audio processing provide a new opportunity to study musical trends using quantitative methods. While past work has investigated trends in music over time, there has been no large-scale study on the evolution of vocal lines. In this work, we conduct an exploratory study of 145,912 vocal tracks of popular songs spanning 55 years, from 1955 to 2010. We use source separation to extract the vocal stem and fundamental frequency (f0) estimation to analyze pitch tracks. Additionally, we extract pitch characteristics including mean pitch, total variation, and pitch class entropy of each song. We conduct statistical analysis of vocal pitch across years and genres, and report significant trends in our metrics over time, as well as significant differences in trends between genres. Our study demonstrates the utility of this method for studying vocals, contributes to the understanding of vocal trends, and showcases the potential of quantitative approaches in musicology.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 73%
Nanoporous metals and alloys
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