Creating an a cappella singing audio dataset for automatic Jingju singing evaluation research

dc.contributor.authorGong, Rong
dc.contributor.authorCaro Repetto, Rafael
dc.contributor.authorSerra, Xavier
dc.date.accessioned2019-05-09T09:31:59Z
dc.date.available2019-05-09T09:31:59Z
dc.date.issued2017
dc.descriptionComunicació presentada al 4th International Workshop on Digital Libraries for Musicology celebrat el 28 d'octubre de 2017 a Shanghai, Xina.
dc.description.abstract e data-driven computational research on automatic jingju (also known as Beijing or Peking opera) singing evaluation lacks a suitable and comprehensive a cappella singing audio dataset. In this work, we present an a cappella singing audio dataset which consists of 120 arias, accounting for 1265 melodic lines. is dataset is also an extension our existing CompMusic jingju corpus. Both professional and amateur singers were invited to the dataset recording sessions, and the most common jingju musical elements have been covered. is dataset is also accompanied by metadata per aria and melodic line annotated for automatic singing evaluation research purpose. All the gathered data is openly available online.
dc.description.sponsorshipThis research was funded by the European Research Council under the European Union's Seventh Framework Program, as part of the CompMusic project (ERC grant agreement 267583).
dc.format.mimetypeapplication/pdf
dc.identifier.citationGong R, Caro Repetto R, Serra X. Creating an a cappella singing audio dataset for automatic Jingju singing evaluation research. In: Proceedings of the 4th International Workshop on Digital Libraries for Musicology; 2017 Oct 28; Shanghai, China. New York: ACM; 2017. p. 37-40. DOI: 10.1145/3144749.3144757
dc.identifier.doihttp://dx.doi.org/10.1145/3144749.3144757
dc.identifier.urihttp://hdl.handle.net/10230/37199
dc.language.isoeng
dc.publisherACM Association for Computer Machinery
dc.relation.ispartofProceedings of the 4th International Workshop on Digital Libraries for Musicology; 2017 Oct 28; Shanghai, China. New York: ACM; 2017. p. 37-40.
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/267583
dc.rights© 2017 Association for Computing Machinery
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.subject.keywordA cappella singing
dc.subject.keywordAutomatic jingju singing evaluation
dc.subject.keywordAudio recording dataset
dc.titleCreating an a cappella singing audio dataset for automatic Jingju singing evaluation research
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.type.versioninfo:eu-repo/semantics/acceptedVersion

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