Probing the underlying principles of dynamics in piano performances using a modelling approach.

Abstract

Variations in dynamics are an essential component of musical performance in most instruments. To study the factors that contribute to dynamic variations, we used a model approaching, allowing for determination of the individual contribution of different musical features. Thirty monophonic melodies from 3 stylistic eras with all expressive markings removed were performed by 20 pianists on a Disklavier piano. The results indicated a relatively high agreement among the pianists (Cronbach's alpha = 0.88). The overall average dynamics (across pianists) could be predicted quite well using support vector regression (R2 = 66%) from a set of 48 score-related features. The highest contribution was from pitch-related features (37.3%), followed by phrasing (12.3%), timing (2.8%), and meter (0.7%). The highest single contribution was from the high-loud principle, whereby higher notes were played louder, as corroborated by the written feedback of many of the pianists. There were also differences between the styles. The highest contribution from phrasing, for example, was obtained from the Romantic examples, while the highest contribution from meter came from the Baroque examples. An analysis of each individual pianist revealed some fundamental differences in approach to the performance of dynamics. All participants were undergraduate-standard pianists or above; however, varied levels of consistency and predictability highlighted challenges in acquiring a reliable group in terms of expertise and preparation, as well as certain pianistic challenges posed by the task. Nevertheless, the method proved useful in disentangling some underlying principles of musical performance and their relation to structural features of the score, with the potential for productive adaptation to a wider range of expressive and instrumental contexts.