潜伏进化特征:分析音乐和文化进化的一般框架
Jonathan Warrell1,2, Leonidas Salichos1,2,3,4, Michael Gancz5
1Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
Journal of the Royal Society, Interface
|March 19, 2024
概括
这项研究引入了一个新的框架来识别音乐中的进化模式,类似于基因组学. 该模型从音乐作品中提取"进化签名",改进了类型和时期的预测.
科学领域:
- 计算音乐学 计算音乐学
- 进化计算是一种进化计算.
- 数字人文学科 数字人文学科
背景情况:
- 文化进化与生物进化有着相似之处.
- 在非生物系统中,特别是音乐中,识别潜在的单位和进化过程仍然具有挑战性.
- 现有的方法缺乏一个框架来共同分析音乐单元及其演化轨迹.
研究的目的:
- 为了引入一个一般的框架来识别音乐的基础单位和进化过程.
- 以音乐风格和组织原则 (和,形式) 为演化过程的模型.
- 从音乐体中提取潜在的进化特征进行分析.
主要方法:
- 开发了一个深层次的生成架构,一个具有进化先验的变异自动编码器.
- 在进化空间中使用基于能量的先前链接歌曲来限制潜伏空间.
- 分析了麦吉尔广告牌数据集中的歌曲,以提取进化签名.
主要成果:
- 在音乐作品中识别了频繁的和弦过渡和正式的重复方案.
- 提取了与和形式特征相关的潜在进化特征.
- 证明进化表征在时期和类型预测任务中优于非进化表征.
结论:
- 拟议的框架成功地模拟了音乐演变,并确定了潜在的进化特征.
- 这些签名为音乐作品提供了有意义的嵌入,增强了分析任务.
- 这种方法通过计算方法为了解音乐的文化演变提供了新的视角.
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