From local markers to global form: ...
Type de document :
Partie d'ouvrage
Titre :
From local markers to global form: Computational modeling of musical structure
Auteur(s) :
Bigo, Louis [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Giraud, Mathieu [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Algomus
Leve, Florence [Auteur]
Modélisation, Information et Systèmes - UR UPJV 4290 [MIS]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Algomus
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Giraud, Mathieu [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Algomus
Leve, Florence [Auteur]
Modélisation, Information et Systèmes - UR UPJV 4290 [MIS]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Algomus
Date de publication :
2021
Discipline(s) HAL :
Sciences de l'Homme et Société/Musique, musicologie et arts de la scène
Informatique [cs]/Son [cs.SD]
Informatique [cs]/Son [cs.SD]
Résumé en anglais : [en]
Musical structure plays an essential role in the listener’s perception of a piece of music. In Western tonal tradition, the structure of a musical score results from a number of factors including repetitions, ...
Lire la suite >Musical structure plays an essential role in the listener’s perception of a piece of music. In Western tonal tradition, the structure of a musical score results from a number of factors including repetitions, variations, and typical harmonic progressions such as cadences. Cadences contribute to the segmentation of the musical discourse into successive phrases by the feeling of closure or relaxation they provide to the listener (Blombach, 1987). Modellng cadences is therefore a promising task to improve our understanding of the perception of musical structure.We present an approach to model cadences, based onautomatic corpus extraction of theory driven features that are commonly used to describe cadences. Experiments on two different corpora from J.-S. Bach and J. Haydn showt that, despite their perceptive salience and apparent univocity, cadences turn out to be challenging to model computationally and variable depending on the musical style.We will then present how the retrieval of local structural markers such as cadences can be extended to target the modeling of large-scale structures and therefore bring new modeling and cognitive challenges. This approach will be illustrated with the computational retrieval of the sonata form which has been intensively used in the classical style.Lire moins >
Lire la suite >Musical structure plays an essential role in the listener’s perception of a piece of music. In Western tonal tradition, the structure of a musical score results from a number of factors including repetitions, variations, and typical harmonic progressions such as cadences. Cadences contribute to the segmentation of the musical discourse into successive phrases by the feeling of closure or relaxation they provide to the listener (Blombach, 1987). Modellng cadences is therefore a promising task to improve our understanding of the perception of musical structure.We present an approach to model cadences, based onautomatic corpus extraction of theory driven features that are commonly used to describe cadences. Experiments on two different corpora from J.-S. Bach and J. Haydn showt that, despite their perceptive salience and apparent univocity, cadences turn out to be challenging to model computationally and variable depending on the musical style.We will then present how the retrieval of local structural markers such as cadences can be extended to target the modeling of large-scale structures and therefore bring new modeling and cognitive challenges. This approach will be illustrated with the computational retrieval of the sonata form which has been intensively used in the classical style.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
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