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Poster Communications Year : 2021

Characterizing Texture for Symbolic Piano Music

Abstract

Musical texture describes how sounding components are organized, individually or with each other. In this work, we propose a new syntax to characterize symbolic texture in classical piano music and thus allow its automated analysis. We annotated the score of 9 movements of W.A. Mozart’s sonatas (totalling 1164 bars), on which tested binary classification models show promising results for automatic texture retrieval.
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Dates and versions

hal-03526689 , version 1 (14-01-2022)

Identifiers

  • HAL Id : hal-03526689 , version 1

Cite

Louis Couturier, Louis Bigo, Florence Levé. Characterizing Texture for Symbolic Piano Music. Digital Music Research Network (DMRN+16), Dec 2021, Londres, United Kingdom. . ⟨hal-03526689⟩
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