使用机器学习对云南葫芦丝（一种中国西南部自由簧管乐器）的音色分析
Timbre Analysis of the Hulusi, a Southwestern Chinese Free-Reed Instrument, using Machine Learning
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- College of Art, Zhejiang Normal University（浙江师范大学艺术学院）
- Institute of Systematic Musicology, University of Hamburg（汉堡大学系统音乐学研究所）
机构由 AI 辅助整理，请以论文原文为准。
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中文总结 AI 辅助
本研究使用机器学习（COMSAR框架中的SOM）分析云南葫芦丝的音色，发现频谱质心、锐度和分形关联维数可形成音高聚类，其中分形维数聚类效果最佳，且最高音高混沌性最低。
中文摘要 AI 辅助
葫芦丝是一种管乐器，发明于中国云南省，近年来变得极为流行。它由一个吹嘴、一个葫芦和三根竹管组成，所有部分都配有铜制自由簧片。中间的主竹管上有七个指孔。在这种乐器中，决定音高的是管长，而非自由簧片的固有频率，这与例如西方手风琴或蓝调口琴不同。在本研究中，使用在COMSAR框架（此 https URL）中实现的机器学习模型来研究葫芦丝的音色特征，以对不同乐器和音高进行聚类。根据七种心理声学特征对实测的葫芦丝音高C、B、A、G和F进行了分析，其中只有频谱质心、锐度和分形关联维数显示出形成音高聚类。这些音色特征被用于训练Kohonen自组织映射（SOM）进行聚类。亮度和锐度分析显示，最高音高不如中音和低音音高亮和锐利。此外，分形关联维数主要决定初始瞬态的混沌程度，是葫芦丝聚类效果最好的音色特征，最高音高显示出最小的混沌性。这一结果通过为SOM定义聚类质量指数得到支持。
英文摘要
The hulusi is a wind instrument that was invented in Yunnan Province, China, and has become tremendously popular in recent years. It consists of a mouthpiece, a gourd, and three bamboo tubes, all with free reeds made of copper. The main bamboo tube in the middle has seven finger holes. In this instrument, the pipe length, not the free reed's eigenfrequency, determines the instrument's pitch, unlike, for example, with the Western accordion or the blues harp. In this study, a machine learning model implemented in the COMSAR framework (https://github.com/ifsm) was used to investigate the timbre characteristics of the \emph{hulusi} to cluster different instruments and pitches. The measured \emph{hulusi} pitches C, B, A, G, and F were analyzed according to seven psychoacoustic features, among which only the spectral centroid, sharpness, and fractal correlation dimension are shown to form pitch clusters. These timbre features were used to train Kohonen self-organizing maps (SOMs) for clustering. Brightness and sharpness analysis revealed that the highest pitches were less bright and less sharp than mid- and low-range pitches were. Furthermore, the fractal correlation dimension, which mainly determines the chaoticity of the initial transients, was the best-clustering timbre feature for the hulusi, with the highest pitches showing the least chaoticity. This result is supported by defining a cluster quality index for the SOMs.
