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对传统音乐应用程序的爪语Gamelan数据集的标记
Arik Kurniawati1,2, Eko Mulyanto Yuniarno1,3, Yoyon Kusnendar Suprapto1,3
1Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia.
Data in brief
|February 26, 2024
概括
这项研究介绍了一个爪语的gamelan符号数据集,包含7个结构的35首歌曲. 这种资源有助于深度学习模型对游戏乐的分类,并促进学习传统的爪游戏歌曲.
科学领域:
- 民族音乐学 民族音乐学
- 音乐信息检索 音乐信息检索
- 计算音乐学 计算音乐学
背景情况:
- 传统的爪歌梅兰音乐符号主要由主旋律组成,这对初学者来说具有挑战性.
- 现有的Gamelan研究严重依赖于音频数据,限制了基于符号的分析和生成的范围.
- 需要一个全面的gamelan乐器符号数据集,以推进对这种音乐传统的计算方法.
研究的目的:
- 为35首歌曲在7个不同的结构中引入Java gamelan符号的新数据集.
- 为各种乐器组提供详细的符号,包括balungan, bonang,peking和结构乐器.
- 促进深度学习模型的开发,用于Gamelan音乐分类和自动符号生成.
主要方法:
- 该数据集汇编了爪语的gamelan gendhing (歌曲) 符号,包括来自gamelanbvg.com.com的主要旋律.
- 乐器组符号是通过遵守已确立的爪游戏规则来创建的.
- 每首歌曲都以一个可移植文档格式 (PDF) 文件中的乐谱形式呈现.
主要成果:
- 一个由35首爪语梅兰歌曲组成的数据集,分为7个结构,并附有详细的乐器符号.
- 数据集包括balungan, bonang,北京和结构乐器组的初级旋律和特定符号.
- 这些标记以PDF格式呈现,为分析和学习提供了一个结构化的资源.
结论:
- 这一数据集为开发深度学习模型的Java gamelan歌曲分类和识别提供了宝贵的资源.
- 数据集支持为类似的歌曲类型自动生成Java gamelan符号.
- 它作为学习爪语梅兰音乐的教育工具,有助于其保存.
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