The Vocal Eras Tour: Microtiming Trends Across Decades and Genres

Recent advancements in audio processing have enabled large-scale, quantitative analysis of musical trends. While previous research has explored changes in music over time, the evolution of vocal performance characteristics remains underexplored. In this work, we analyze the microtiming of 88,357 vocal tracks from popular songs spanning 45 years (1965–2010). Using source-separated vocal stems, we analyze vocal timing deviations in songs with a duple metrical structure at both the beat (quarter-note) and beat subdivision (16th-note) levels. We identify vocal onsets to study microtiming deviations. Through statistical analysis, we find significant differences in microtiming between musical genres, as well as trends over time. Our analysis reveals that Rap music has the greatest number of vocal onsets on average, generally arriving later than those of other genres. Across the other genres, singers tend to anticipate the beat, especially on beats 1 and 3. However, these entries have shifted closer to metrical targets over time, possibly reflecting the influence of digital editing tools and evolving listener preferences. Our findings demonstrate the utility of quantitative analysis methods for studying vocal timing and contribute new insights to the understanding of how singing voice recordings have evolved in popular music. We believe these methods have the potential to be applied to the study of other instruments and more diverse musical styles.