Das Gesamtkunstwerk Oper aus Datensicht

Röwenstrunk, Daniel; Prätzlich, Thomas; Betzwieser, Thomas; Müller, Meinard; Szwillus, Gerd; Veit, Joachim

doi:10.1007/s13222-015-0179-0

Cited by 5 publications

(6 citation statements)

References 4 publications

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“…Concerning opera in general, a few datasets have been published on shorter works such as Mozart's Zauberflöte 5 or Weber's Freischütz. 6 MIR studies dealing with such earlier operas like Don Giovanni (Brazier and Widmer, 2021) or Freischütz (Röwenstrunk et al, 2015;Prätzlich and Müller, 2013) face challenges due to performance differences of the number operas, which lead to structural mismatches posing problems for music synchronization and tracking. Thanks to the throughcomposed style, the Ring is widely free of such structural problems but comes with other challenges.…”

Section: Background and Related Workmentioning

confidence: 99%

“…While the field has mostly focused on piano (Hawthorne et al, 2019) and chamber music (Thickstun et al, 2017), opera is an interesting yet challenging scenario (Röwenstrunk et al, 2015;Prätzlich and Müller, 2013), where one has to deal with various modalities regarding the libretto (text), the composition (image, symbolic), and the performances (audio, video) as well as with the large extent of these works, which often last for several hours-a tremendous contrast to the 3-5 minutes duration of most pop songs. One of the most extensive works is the tetralogy Der Ring des Nibelungen, being created by Richard Wagner between 1848 and 1874 and comprising four operas (which Wagner called music dramas).…”

Section: Introductionmentioning

confidence: 99%

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Wagner Ring Dataset: A Complex Opera Scenario for Music Processing and Computational Musicology

Weiß,

Arifi-Müller,

Krause

et al. 2023

Transactions of the International Society for Music Information Retrieval

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This paper introduces the Wagner Ring Dataset (WRD), a multi-modal and multiversion 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.

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Section: Background and Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Wagner Ring Dataset: A Complex Opera Scenario for Music Processing and Computational Musicology

Weiß,

Arifi-Müller,

Krause

et al. 2023

Transactions of the International Society for Music Information Retrieval

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, the interdisciplinary field of computational musicology requires platforms beyond data repositories, which support a crossdisciplinary scientific exchange by offering a direct, intuitive, and comprehensive access to the data. This can be accomplished by means of interactive interfaces that bridge the gap between the musicological and the audio domain (e.g., see Gasser et al, 2015;Jeong et al, 2017;Röwenstrunk et al, 2015).…”

Section: Web-based Interfacementioning

confidence: 99%

Erkomaishvili Dataset: A Curated Corpus of Traditional Georgian Vocal Music for Computational Musicology

Rosenzweig¹,

Scherbaum²,

Shugliashvili³

et al. 2020

Transactions of the International Society for Music Information Retrieval

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The analysis of recorded audio material using computational methods has received increased attention in ethnomusicological research. We present a curated dataset of traditional Georgian vocal music for computational musicology. The corpus is based on historic tape recordings of three-voice Georgian songs performed by the the former master chanter Artem Erkomaishvili. In this article, we give a detailed overview of the audio material, transcriptions, and annotations contained in the dataset. Beyond its importance for ethnomusicological research, this carefully organized and annotated corpus constitutes a challenging scenario for music information retrieval tasks such as fundamental frequency estimation, onset detection, and score-to-audio alignment. The corpus is publicly available and accessible through score-following web-players.

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“…The interdisciplinary field of MIR benefits from interfaces that help to lower access barriers to datasets by providing direct, intuitive, and comprehensive access. This can be accomplished by means of interactive interfaces, e.g., with playback functionalities (Gasser et al, 2015;Jeong et al, 2017;Röwenstrunk et al, 2015). As one contribution, we created a publicly accessible web-based interface, 8 which hosts the multitrack audio data.…”

Section: Dagstuhl Choirset Interfacesmentioning

confidence: 99%

Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing

Rosenzweig

Cuesta

Weiß

et al. 2020

Transactions of the International Society for Music Information Retrieval

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Choral singing is a central part of musical cultures across the world, yet many facets of this widespread form of polyphonic singing are still to be explored. Music information retrieval (MIR) research on choral singing benefits from multitrack recordings of the individual singing voices. However, there exist only few publicly available multitrack datasets on polyphonic singing. In this paper, we present Dagstuhl ChoirSet (DCS), a multitrack dataset of a cappella choral music designed to support MIR research on choral singing. The dataset includes recordings of an amateur vocal ensemble performing two choir pieces in full choir and quartet settings. The audio data was recorded during an MIR seminar at Schloss Dagstuhl using different close-up microphones to capture the individual singers' voices. In this article, we give detailed insights into all stages of creating DCS: recording process, data preparation, generation of annotations as well as development of suitable interfaces for publicly accessing and reusing the data. Furthermore, we demonstrate the potential of the dataset for MIR research by discussing case studies on choral intonation assessment and multiple fundamental frequency (F0) estimation.

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Das Gesamtkunstwerk Oper aus Datensicht

Cited by 5 publications

References 4 publications

Wagner Ring Dataset: A Complex Opera Scenario for Music Processing and Computational Musicology

Wagner Ring Dataset: A Complex Opera Scenario for Music Processing and Computational Musicology

Erkomaishvili Dataset: A Curated Corpus of Traditional Georgian Vocal Music for Computational Musicology

Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing

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