Towards computer-assisted understanding of dynamics in symphonic music

TL;DR

This paper presents a computational model that analyzes expressive loudness variations in symphonic music performances, aiming to understand interpretative differences among conductors and enhance music appreciation tools.

Contribution

It introduces a novel model linking musical scores to performance dynamics, highlighting interpretative differences and providing a foundation for interactive music understanding.

Findings

Model predicts expressive loudness variations effectively

Identifies conductor-specific interpretative patterns

Potential for developing interactive music analysis tools

Abstract

Many people enjoy classical symphonic music. Its diverse instrumentation makes for a rich listening experience. This diversity adds to the conductor's expressive freedom to shape the sound according to their imagination. As a result, the same piece may sound quite differently from one conductor to another. Differences in interpretation may be noticeable subjectively to listeners, but they are sometimes hard to pinpoint, presumably because of the acoustic complexity of the sound. We describe a computational model that interprets dynamics---expressive loudness variations in performances---in terms of the musical score, highlighting differences between performances of the same piece. We demonstrate experimentally that the model has predictive power, and give examples of conductor ideosyncrasies found by using the model as an explanatory tool. Although the present model is still in active development, it may pave the road for a consumer-oriented companion to interactive classical music understanding.