Analysis of Musical Dynamics in Vocal Performances Using Loudness Measures

Jyoti Narang; Marius Miron; Ajay Srinivasamurthy; Xavier Serra
DAFx-2022 - Vienna
In addition to tone, pitch and rhythm, dynamics is one of the expressive dimensions of the performance of a music piece that has received limited attention. While the usage of dynamics may vary from artist to artist, and also from performance to performance, a systematic methodology to automatically identify the dynamics of a performance in terms of musically meaningful terms like forte, piano may offer valuable feedback in the context of music education and in particular in singing. To this end, we have manually annotated the dynamic markings of commercial recordings of popular rock and pop songs from the Smule Vocal Balanced (SVB) dataset which will be used as reference data. Then as a first step for our research goal, we propose a method to derive and compare singing voice loudness curves in polyphonic mixtures. Towards measuring the similarity and variation of dynamics, we compare the dynamics curves of the SVB renditions with the one derived from the original songs. We perform the same comparison using professionally produced renditions from a karaoke website. We relate high values of Spearman correlation coefficient found in some select student renditions and the professional renditions with accurate dynamics.