Title :

Modeling and learning structural breaks in sonata forms

Author(s) :

Feisthauer, Laurent [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Algomus
Bigo, Louis [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Algomus
Giraud, Mathieu [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Algomus

Conference title :

International Society for Music Information Retrieval Conference (ISMIR 2019)

City :

Delft

Country :

Pays-Bas

Start date of the conference :

2019

Journal title :

International Society for Music Information Retrieval Conference (ISMIR 2019)

English keyword(s) :

Music Information Retrieval
sonata form
medial caesura
cadence
harmony
machine learning

HAL domain(s) :

Sciences de l'Homme et Société/Musique, musicologie et arts de la scène
Informatique [cs]/Son [cs.SD]
Informatique [cs]/Apprentissage [cs.LG]

English abstract : [en]

Expositions of Sonata Forms are structured towards two cadential goals, one being the Medial Caesura (MC). The MC is a gap in the musical texture between the Transition zone (TR) and the Secondary thematic zone (S). It ...
Show more >Expositions of Sonata Forms are structured towards two cadential goals, one being the Medial Caesura (MC). The MC is a gap in the musical texture between the Transition zone (TR) and the Secondary thematic zone (S). It appears as a climax of energy accumulation initiated by the TR, dividing the Exposition in two parts. We introduce high-level features relevant to formalize this energy gain and to identify MCs. These features concern rhythmic, harmonic and textural aspects of the music and characterize either the MC, its preparation or the texture contrast between TR and S. They are used to train a LSTM neural network on a corpus of 27 movements of string quartets written by Mozart. The model correctly locates the MCs on 14 movements within a leave-one-piece-out validation strategy. We discuss these results and how the network manages to model such structural breaks.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL