Subject and counter-subject detection for analysis of the Well-Tempered Clavier fugues

Abstract : Fugue analysis is a challenging problem. We propose an algorithm that detects subjects and counter-subjects in a symbolic score where all the voices are separated, determining the precise ends and the occurrence positions of these patterns. The algorithm is based on a diatonic similarity between pitch intervals combined with a strict length matching for all notes, except for the first and the last one. On the 24 fugues of the first book of Bach's Well-Tempered Clavier, the algorithm predicts 66% of the subjects with a musically relevant end, and finally retrieves 85% of the subject occurrences, with almost no false positive.
Type de document :
Communication dans un congrès
International Symposium on Computer Music Modelling and Retrieval (CMMR 2012), 2012, United Kingdom. pp.661-673, 2012


https://hal.archives-ouvertes.fr/hal-00712554
Contributeur : Mathieu Giraud <>
Soumis le : mercredi 27 juin 2012 - 11:56:45
Dernière modification le : vendredi 8 janvier 2016 - 01:07:09

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  • HAL Id : hal-00712554, version 1

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Mathieu Giraud, Richard Groult, Florence Levé. Subject and counter-subject detection for analysis of the Well-Tempered Clavier fugues. International Symposium on Computer Music Modelling and Retrieval (CMMR 2012), 2012, United Kingdom. pp.661-673, 2012. <hal-00712554>

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