Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing
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, t...
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doaj-2a82220a48cf4316834f9ea01f00ed922020-11-25T03:37:54ZengUbiquity PressTransactions of the International Society for Music Information Retrieval2514-32982020-07-013110.5334/tismir.4827Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral SingingSebastian Rosenzweig0Helena Cuesta1Christof Weiß2Frank Scherbaum3Emilia Gómez4Meinard Müller5International Audio Laboratories ErlangenMusic Technology Group, Universitat Pompeu Fabra, BarcelonaInternational Audio Laboratories ErlangenUniversity of PotsdamMusic Technology Group, Universitat Pompeu Fabra, Barcelona; Joint Research Centre, European Commission, SevilleInternational Audio Laboratories ErlangenChoral 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.https://transactions.ismir.net/articles/48dagstuhl choirsetchoral musicmultitrack recordingchoral singing analysisf0 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sebastian Rosenzweig Helena Cuesta Christof Weiß Frank Scherbaum Emilia Gómez Meinard Müller |
spellingShingle |
Sebastian Rosenzweig Helena Cuesta Christof Weiß Frank Scherbaum Emilia Gómez Meinard Müller Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing Transactions of the International Society for Music Information Retrieval dagstuhl choirset choral music multitrack recording choral singing analysis f0 |
author_facet |
Sebastian Rosenzweig Helena Cuesta Christof Weiß Frank Scherbaum Emilia Gómez Meinard Müller |
author_sort |
Sebastian Rosenzweig |
title |
Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing |
title_short |
Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing |
title_full |
Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing |
title_fullStr |
Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing |
title_full_unstemmed |
Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing |
title_sort |
dagstuhl choirset: a multitrack dataset for mir research on choral singing |
publisher |
Ubiquity Press |
series |
Transactions of the International Society for Music Information Retrieval |
issn |
2514-3298 |
publishDate |
2020-07-01 |
description |
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. |
topic |
dagstuhl choirset choral music multitrack recording choral singing analysis f0 |
url |
https://transactions.ismir.net/articles/48 |
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