用机器学习发现西式甘美兰演奏更规律，印尼式更自由。
Clustering of Indonesian and Western Gamelan Orchestras through Machine Learning of Performance Parameters
- 用自组织映射分析音高与音色特征，识别演奏差异。
- 西方甘美兰演奏在发音和整体结构上变化较少。
- 适合对音乐人类学或跨文化音乐研究感兴趣者。
本文通过分析四支西方与五支印尼甘美兰乐团的录音，研究其演奏差异。采用自组织柯霍嫩映射（SOM）机器学习算法，基于音高系统与音色特征进行分析。结果显示，在某些心理声学特征上，西方与印尼乐团形成明显聚类；西方乐团在发音方式和大型结构变化上显著减少，表现出更低的可变性。而在音高系统方面未发现东西方之间的聚类差异。这表明西方对甘美兰的接受与演绎更趋向于简化、中介化与平静，反映其历史上的异域化倾向。
原文摘要 · Abstract (English)
Indonesian and Western gamelan ensembles are investigated with respect to performance differences. Thereby, the often exotistic history of this music in the West might be reflected in contemporary tonal system, articulation, or large-scale form differences. Analyzing recordings of four Western and five Indonesian orchestras with respect to tonal systems and timbre features and using self-organizing Kohonen map (SOM) as a machine learning algorithm, a clear clustering between Indonesian and Western ensembles appears using certain psychoacoustic features. These point to a reduced articulation and large-scale form variability of Western ensembles compared to Indonesian ones. The SOM also clusters the ensembles with respect to their tonal systems, but no clusters between Indonesian and Western ensembles can be found in this respect. Therefore, a clear analogy between lower articulatory variability and large-scale form variation and a more exostistic, mediative and calm performance expectation and reception of gamelan in the West therefore appears.
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