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Conference Papers Year : 2022

A Dataset of Symbolic Texture Annotations in Mozart Piano Sonatas

Abstract

Musical scores are generally analyzed under different aspects, notably melody, harmony, rhythm, but also through their texture, although this last concept is arguably more delicate to formalize. Symbolic texture depicts how sounding components are organized in the score. It outlines the density of elements, their heterogeneity, role and interactions. In this paper, we release a set of manual annotations for each bar of 9 movements among early piano sonatas by W. A. Mozart, totaling 1164 labels that follow a syntax dedicated to piano score texture. A quantitative analysis of the annotations highlights some characteristic textural features in the corpus. In addition, we present and release the implementation of low-level descriptors of symbolic texture, that are preliminary experimented for textural elements prediction. The annotations and the descriptors offer promising applications in computer-assisted music analysis and composition.
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hal-03860195 , version 1 (18-11-2022)

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Louis Couturier, Louis Bigo, Florence Levé. A Dataset of Symbolic Texture Annotations in Mozart Piano Sonatas. International Society for Music Information Retrieval Conference (ISMIR 2022), Dec 2022, Bengaluru, India. ⟨10.5281/zenodo.7316712⟩. ⟨hal-03860195⟩
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