ALGORITHMIC ANALYSIS AND HARMONIC DATABASE GENERATION FOR MUSICOLOGISTS
ANALYSE ALGORITHMIQUE ET GÉNÉRATION DE BASES DE DONNÉES HARMONIQUES POUR LES MUSICOLOGUES
Résumé
Harmony is an integral part of both the musicology and conservatory curricula. This article discusses some technical aspects of the "Learning Harmonizer" project aiming at developing a pedagogical tool for the hybrid teaching of this discipline. It can be used by teachers in class to help students complete exercises on their own, or to correct exercises on blackboards. In fact, in addition to a hybrid classroom, the tool will offer hybrid teaching with e-learning. Students will be able to do their homework with the help of the tool, which will help them complete all the exercises, even if they have difficulty. The teacher will also be able to monitor students' personal investment and performance in their work at home and in class. This will make it easier for the teacher to know which students are struggling, giving up or to identify notions not acquired by a majority. For this purpose, it is necessary to work on large corpora. But, analyzing and studying an entire corpus takes a lot of time and energy, which is why we have developed tools that do this automatically. This article presents two modules of this projet, one to analyze many scores, and the other to extract the harmonic sequences used by the composers of the scores. The Music toolbox [1] is used to analyse the scores, and an oracle is built using the VMO library [2] to extract the harmonic sequences. We analyze tones, modulations, chords and foreign notes. And we transcribe these analyses into Baroque and Anglo-Saxon notation. This tool can be used independently of the harmony teaching tool. Indeed, it could be used to teach musical analysis, another subject in the curriculum. In addition to their usefulness in the Learning Harmonizer project, they enable the automatic generation of databases of analyzed scores and chord sequences appropriate to the composer's writing style. These databases can be used by musicologists and other computer music researchers for their projects and teaching.
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