基于人和计算的佳美兰音乐表示

IF 0.2 N/A MUSIC Malaysian Journal of Music Pub Date : 2020-11-20 DOI:10.37134/MJM.VOL9.7.2020
A. M. Syarif, A. Azhari, S. Suprapto, K. Hastuti
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引用次数: 7

摘要

需要一个包含卡拉维坦传统音乐代表性数据的公共数据库,作为研究计算机音乐和卡拉维坦的研究人员的资源。为了建立这个数据库,我们首先研究了一个基于文本的音乐音高模型,该模型既基于人类,也基于计算机。一种可以被人类和计算机读懂的音乐表现的新模型被提出,以支持卡拉维坦音乐和计算机研究,也被称为甘美兰音乐。该模型有望作为建立卡拉维坦音乐表现数据公共数据库的初步努力。所提出的模型受到亥姆霍兹记谱法和科学音高记谱法以及完善的基于文本的音高表示系统的启发。该模型不仅适用于音高数字、高或低或中音高信息(八度信息),而且适用于甘美兰乐谱中包含音高值和连音符号的音乐元素。该模型被命名为gending Scientific Pitch Notation (GSPN)。歌定是爪哇语,意思是“歌”。GSPN模型被设计为通过从乐谱中形成音乐元素来表示音乐。此外,该模型还可以自动转换为其他音乐表示格式。在实验中,利用局部表示技术实现了GSPN格式的数据自动转换乐谱为二进制码。
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Human and Computation-based Music Representation for Gamelan Music
A public database containing representative data of karawitan traditional music is needed as a resource for researchers who study computer music and karawitan. To establish this database, a text-based pitch model for music representation that is both human and computer-based was first investigated. A new model of musical representation that can be read by humans and computers is proposed to support music and computer research on karawitan also known as gamelan music. The model is expected to serve as the initial effort to establish a public database of karawitan music representation data. The proposed model was inspired by Helmholtz Notation and Scientific Pitch Notation and well-established, text-based pitch representation systems. The model was developed not only for pitch number, high or low or middle pitch information (octave information), but for musical elements found in gamelan sheet music pieces that include pitch value and legato signs. The model was named Gendhing Scientific Pitch Notation (GSPN). Ghending is a Javanese word that means “song”. The GSPN model was designed to represent music by formulating musical elements from a sheet music piece. Furthermore, the model can automatically be converted to other music representation formats. In the experiment, data in the GSPN format was implemented to automatically convert sheet music to a binary code with localist representation technique.
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来源期刊
CiteScore
0.40
自引率
50.00%
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