Music Interpretation Analysis. A Multimodal Approach To Score-Informed Resynthesis of Piano Recordings

TL;DR

This thesis introduces a novel framework called Music Interpretation Analysis (MIA) for understanding and resynthesizing piano recordings by considering acoustic context and performer intent, advancing digital music production tools.

Contribution

It presents a new conceptual and mathematical framework for music interpretation analysis, enabling improved score-informed resynthesis of recordings.

Findings

Preliminary evaluations show the effectiveness of the MIA framework.

Development of software and datasets for historical music archiving.

Extensions of MIP technologies for better music resynthesis.

Abstract

This Thesis discusses the development of technologies for the automatic resynthesis of music recordings using digital synthesizers. First, the main issue is identified in the understanding of how Music Information Processing (MIP) methods can take into consideration the influence of the acoustic context on the music performance. For this, a novel conceptual and mathematical framework named "Music Interpretation Analysis" (MIA) is presented. In the proposed framework, a distinction is made between the "performance" - the physical action of playing - and the "interpretation" - the action that the performer wishes to achieve. Second, the Thesis describes further works aiming at the democratization of music production tools via automatic resynthesis: 1) it elaborates software and file formats for historical music archiving and multimodal machine-learning datasets; 2) it explores and extends MIP technologies; 3) it presents the mathematical foundations of the MIA framework and shows preliminary evaluations to demonstrate the effectiveness of the approach