Traitement de la polyphonie pour l’analyse informatique de partitions musicales

Nicolas Guiomard-Kagan 1, 2
2 Algomus
MIS - Modélisation, Information & Systèmes, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : Music can be either monophonic (a single note sounds at each time) or polyphonic (several notes are sounding simultaneously, building harmonies). Understanding polyphonic music can be very complex. The goal of this thesis in computer music is to ease the analysis of polyphonic scores by splitting them in either monophonic voices or streams (coherent sets of notes). Research in this thesis first consists in comparing three voices separation algorithms and three streams separation algorithms. I propose an evaluation method to fairly compare these two approaches. This study shows the qualities of the Chew and Wu algorithm. The first step of this algorithm, which segments the score into “contigs” having a constant number of voices, is particularly robust. Further work of this thesis focuses on the second stage of the Chew and Wu algorithm that defines what contigs to connect and how to connect them. I improve these connections by using musical parameters such as the average pitch difference between neighbor contigs. The thesis concludes by evaluating simultaneously voice separation and pattern matching for the music analysis of fugues.
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Submitted on : Wednesday, October 18, 2017 - 6:32:52 PM
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Nicolas Guiomard-Kagan. Traitement de la polyphonie pour l’analyse informatique de partitions musicales. Informatique [cs]. Université de Picardie - Jules Verne, 2017. Français. ⟨tel-01618983⟩

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