Weiß C, Arifi-Müller V, Krause M, Zalkow F, Klauk S, Kleinertz R, Müller M (2023)
Publication Type: Journal article
Publication year: 2023
Book Volume: 6
Pages Range: 135-149
Issue: 1
Journal Issue: 1
DOI: 10.5334/tismir.161
This paper introduces the Wagner Ring Dataset (WRD), a multi-modal and multi-version resource on the large-scale opera cycle Der Ring des Nibelungen by Richard Wagner. The Ring comprises four music dramas organized into eleven acts and 21 939 measures in total. Concerning sheet music, we processed a publicly available piano reduction (822 pages) of the full score with optical music recognition followed by extensive manual corrections to create a high-quality, machine-readable symbolic score. Concerning audio data, our corpus covers 16 recorded performances of the full Ring (three of which are publicly available thanks to copyright expiry), each lasting about 14–15 hours. To musically synchronize these versions among each other, we manually annotated all measure positions for three performances, which we transferred to the remaining performances via automated synchronization techniques. The dataset further comprises annotations of key and time signatures, scenes, and singing voice regions (libretto). Moreover, we provide note event annotations for all performances derived from the piano score. The WRD thus constitutes a comprehensive resource for developing algorithms for various music information retrieval tasks, complementing existing datasets with a complex opera scenario. For computational musicology, the WRD serves as a structured dataset that allows for studying the composition and performances of the Ring.
APA:
Weiß, C., Arifi-Müller, V., Krause, M., Zalkow, F., Klauk, S., Kleinertz, R., & Müller, M. (2023). Wagner Ring Dataset: A Complex Opera Scenario for Music Processing and Computational Musicology. Transactions of the International Society for Music Information Retrieval, 6(1), 135-149. https://doi.org/10.5334/tismir.161
MLA:
Weiß, Christof, et al. "Wagner Ring Dataset: A Complex Opera Scenario for Music Processing and Computational Musicology." Transactions of the International Society for Music Information Retrieval 6.1 (2023): 135-149.
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