Jingju Music Scores Collection
The Jingju Music Scores Collection (JMSC) is part of the Jingju Music Corpus created in the CompMusic project. C
The Jingju Music Scores Collection (JMSC) is part of the Jingju Music Corpus created in the CompMusic project. Created with the purpose of the melodic research of jingju singing lines, it contains 108 MusicXMLscores, covering 1084 melodic lines. In terms of the jingju musical system, it covers the following elements:
- role type: laosheng, dan, laodan
- shengqiang: erhuang, xipi, nanbangzi, sipingdiao
- banshi: manban, sanyan, zhongsanyan, kuaisanyan, yuanban, erliu, kuai'erliu, liushui, kuaiban
The provided README.md file contains details about the content of the JMSC in terms of scores, and in terms of lines.
The scores are sourced from printed editions and created with MuseScore 2.1.0, including the lyrics. The original jianpu notation is transnotated into staff notation. All the scores contain a separated staff for the accompaniment (jinghu) line.
Content of the JMSC
The JMSC contains the following three folders:
- The
MusicXMLfolder contains the MusicXML scores and thescores_data.csvandlines_data.csvfiles containing metadata and annotations. - The
MuseScorefolder contains the scores created with MusicScore in its original format, from which the MusicXML scores were exported.
Annotations and metadata
The MusicXML folder of the JMSC contains the following two files with annotations and metadata.
- The
scores_data.csvfile contains metadata and annotations for each score. The included information consists of the following data: title of the aria (in Chinese), role type, shengqiang, banshi, 'yes' or 'no' the original score contained a separated line for the accompaniment, the reference to the printed source, and the MusicBrainz ID of related recordings. - The
lines_data.csvfile contains annotations for each line in the JMSC. The included information consists of the following data: role type, shengqiang, b
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Files are hosted on the source repository. Click download to access the full dataset.