当前人工智能在音乐方面的研究和应用主要集中在西方古典音乐和流行音乐等领域。以世界各地的传统音乐为对象的相关研究仍然处于初级阶段，其中一个主要原因是缺乏高质量的数据集和标注规范。文章从数据的内容、标注和应用等方面，探讨了传统音乐标注数据集的发展现状。基于对当前研究的深入分析，文章提出了面向人工智能的音乐标注数据集的构建原则，并针对传统音乐的特点加以阐述。在此基础上，以第一个中国胡琴音乐标注数据集（CCOM-HuQin）为例介绍了数据集在人工智能领域的研究成果和应用前景。文章强调了人工智能应用于传统音乐的意义不仅在于辅助创作和表演，更是为了促进传统音乐的保护、传承和发展。

The research and application of artificial intelligence(AI)in music have primarily focused on Western classical and popular music,while studies on traditional music from diverse global cultures are relatively insufficient.One main reason is the lack of high-quality datasets and annotation standards.In this paper,we explore the ongoing development of traditional music datasets from the perspectives of data content,annotation and application.Based on the in-depth analysis of the previous studies,we propose for the first time the construction principles for annotated music datasets aimed at artificial intelligence research,specifically addressing the characteristics of traditional music.According to this,we have constructed the first multimodal performance dataset of HuQin music (CCOM-HuQin),and take it as an example to demonstrate the research outcomes and application prospects of datasets in music AI.This paper emphasizes that the significance of applying AI to traditional music lies not only in assisting with composition and performance,but also in promoting the preservation,inheritance and development of traditional music.