Titre :

MCMA: A Symbolic Multitrack Contrapuntal Music Archive

Auteur(s) :

Aljanaki, Anna [Auteur]
University of Tartu
Kalonaris, Stefano [Auteur]
RIKEN Center for Advanced Intelligence Project [Tokyo] [RIKEN AIP]
Micchi, Gianluca [Auteur]
Modélisation, Information et Systèmes - UR UPJV 4290 [MIS]
Algomus
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Nichols, Eric [Auteur]

Titre de la revue :

Empirical Musicology review

Pagination :

99-105

Éditeur :

Ohio State University Libraries

Date de publication :

2021

ISSN :

1559-5749

Mot(s)-clé(s) en anglais :

counterpoint
polyphony
computational musicology
neural machine translation
symbolic music

Discipline(s) HAL :

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

Résumé en anglais : [en]

We present Multitrack Contrapuntal Music Archive (MCMA, available at https://mcma.readthedocs.io), a symbolic dataset of pieces specifically curated to comprise, for any given polyphonic work, independent voices. So far, ...
Lire la suite >We present Multitrack Contrapuntal Music Archive (MCMA, available at https://mcma.readthedocs.io), a symbolic dataset of pieces specifically curated to comprise, for any given polyphonic work, independent voices. So far, MCMA consists only of pieces from the Baroque repertoire but we aim to extend it to other contrapuntal music. MCMA is FAIR-compliant and it is geared towards musicological tasks such as (computational) analysis or education, as it brings to the fore contrapuntal interactions by explicit and independent representation. Furthermore, it affords for a more apt usage of recent advances in the field of natural language processing (e.g., neural machine translation). For example, MCMA can be particularly useful in the context of language based machine learning models for music generation. Despite its current modest size, we believe MCMA to be an important addition to online contrapuntal music databases, and we thus open it to contributions from the wider community, in the hope that MCMA can continue to grow beyond our efforts. In this article, we provide the rationale for this corpus, suggest possible use cases, offer an overview of the compiling process (data sourcing and processing), and present a brief statistical analysis of the corpus at the time of writing. Finally, future work that we endeavor to undertake is discussed.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

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

Source :

Harvested from HAL