Title:
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Understanding the expressive functions of jingju metrical patterns through lyrics text mining
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Author:
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Zhang, Shuo; Caro Repetto, Rafael; Serra, Xavier
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Abstract:
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Comunicació presentada al MediaEval 2017 Workshop celebrat a Suzhou, Xina, del 23 al 27 d'octubre de 2017. |
Abstract:
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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. |
Abstract:
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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). |
Subject(s):
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-Corpus based research -Document classification -Jingju lyrics -Jingju music -Natural language processing -Topic modeling |
Rights:
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© 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.
http://creativecommons.org/licenses/by/4.0/ |
Document type:
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Conference Object Article - Published version |
Published by:
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International Society for Music Information Retrieval (ISMIR)
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