###### Abstract  
This study focuses on the construction and evaluation of a high-quality Chinese Manchu music dataset designed to facilitate Artificial Intelligence (AI) research and applications within cultural heritage and ethnomusicology. Through a systematic collection and organization of diverse Manchu music resources, including folk songs, dance music, and ceremonial pieces, this dataset effectively represents the cultural breadth of Manchu music. The dataset includes digitized and preprocessed audio data, with comprehensive metadata annotations, such as essential information, musical features, and cultural context, creating a robust foundation for AI-based analysis. Experimental evaluations highlight the dataset's utility across various AI-driven applications: in music classification, using a CNN model, an accuracy of 90% was achieved in the \"folk ensemble\" category, with an overall accuracy of 85.7% and a precision of 82.3%. For music generation, a Generative Adversarial Network (GAN) model yielded a quality score of 7.8/10 and a Frechet Audio Distance (FAD) of 0.32. In emotion recognition, the Random Forest model achieved 87% accuracy in identifying the emotion \"joy\". These results underscore the dataset's potential in supporting digital preservation and expanding AI applications in ethnic music classification, generation, and emotional analysis, contributing to both cultural heritage preservation and AI advancement in ethnomusicology. M +
Footnote †: journal: applied sciences  
0000-0001-5000-0000-0000-0000-0000-0000-0000-0000-0000-0000-00000-00000-0  
across generations. This role is particularly pronounced among ethnic minority groups, where music often holds ceremonial, social, and educational functions that are integral to community cohesion and identity [4; 5; 6]. For the Manchu people--one of China's ethnic minorities with a rich and complex cultural legacy--traditional music represents an invaluable aspect of their heritage [7]. Historically, Manchu music was central to rituals, community gatherings, and even royal ceremonies, especially during the [PERSON] dynasty (1644-1912) when the Manchu people held political power. The roots of Manchu culture can be traced back to the early Jurchen tribes of the 10 th century, who later unified under the leadership of [PERSON] in the early 17 th century to establish the Later Jin Dynasty, which eventually became the Qing Dynasty. However, with the spread of modern cultural influences and shifts in social dynamics, traditional Manchu music faces a significant risk of decline [8; 9]. As younger generations become increasingly distanced from their cultural roots, the practice and transmission of this music are diminishing, making preservation efforts both urgent and complex. The limited availability of resources, recorded materials, and professional documentation further complicates efforts to preserve this unique musical tradition. The diminishing influence of Manchu music is attributed to urbanization, the dominance of mainstream Han culture, and a general shift towards more contemporary musical forms [10; 11; 12]. To provide additional context, Figure 1[13] below presents a geographical map of Northeast China, illustrating the traditional settlement areas of the Manchu people, including key regions such as Jilin, Liaoning, and Heilongjiang provinces, which historically formed the heartland of Manchu culture. The Manchus, who number about 4.2 million in China today, serve as a warning to China's ethnic minorities to protect their culture and language, as only about 50 people still speak their native Manchu language. The advancement of AI technologies provides a promising solution to these challenges by creating systematic, scalable methods for documenting, analyzing, and preserving ethnic music [14; 15; 16]. AI applications in ethnomusicology allow for the detailed capture of audio data, the automatic extraction of musical features, and the generation of new musical compositions that reflect traditional styles.