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Understanding the expressive functions of jingju metrical patterns through lyrics text mining

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dc.contributor.author Zhang, Shuo
dc.contributor.author Caro Repetto, Rafael
dc.contributor.author Serra, Xavier
dc.date.accessioned 2017-07-27T13:10:21Z
dc.date.available 2017-07-27T13:10:21Z
dc.date.issued 2017
dc.identifier.citation Zhang S, Caro Repetto R, Serra X. Understanding the expressive functions of jingju metrical patterns through lyrics text mining. In: Hu X, Cunningham SJ, Turnbull D, Duan Z. ISMIR 2017 Proceedings of the 18th International Society for Music Information Retrieval Conference; 2017 Oct 23-27; Suzhou, China. [Suzhou]: ISMIR; 2017. 397-403.
dc.identifier.uri http://hdl.handle.net/10230/32652
dc.description Comunicació presentada al MediaEval 2017 Workshop celebrat a Suzhou, Xina, del 23 al 27 d'octubre de 2017.
dc.description.abstract The emotional content of jingju (aka Beijing or Peking opera) arias is conveyed through pre-defined metrical patterns known as banshi, each of them associated with a specific expressive function. In this paper, we first report the work on a comprehensive corpus of jingju lyrics that we built, suitable for text mining and text analysis in a data-driven framework. Utilizing this corpus, we propose a novel approach to study the expressive functions of banshi by applying text analysis techniques on lyrics. First we apply topic modeling techniques to jingju lyrics text documents grouped at different levels according to the banshi they are associated with. We then experiment with several different document vector representations of lyrics in a series of document classification experiments. The topic modeling results showed that sentiment polarity (positive or negative) is better distinguished between different shengqiang-banshi (a more fine grained partition of banshi) than banshi alone, and we are able to achieve high accuracy scores in classifying lyrics documents into different banshi categories. We discuss the technical and musicological implications and possible future improvements.
dc.description.sponsorship This research is funded by the European Research Council under the European Union’s Seventh Framework Program (FP7/2007- 2013), as part of the CompMusic project (ERC grant agreement 267583).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher International Society for Music Information Retrieval (ISMIR)
dc.rights © Shuo Zhang, Rafael Caro Repetto, Xavier Serra. Licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Attribution: Shuo Zhang, Rafael Caro Repetto, Xavier Serra. “Understanding the expressive functions of jingju metrical patterns through lyrics text mining ”, 18th International Society for Music Information Retrieval Conference, Suzhou, China, 2017.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title Understanding the expressive functions of jingju metrical patterns through lyrics text mining
dc.type info:eu-repo/semantics/conferenceObject
dc.subject.keyword Corpus based research
dc.subject.keyword Document classification
dc.subject.keyword Jingju lyrics
dc.subject.keyword Jingju music
dc.subject.keyword Natural language processing
dc.subject.keyword Topic modeling
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/267583
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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