This scholarly endeavor, employing cross-cultural and computational methodologies, delves into the perception and interpretation of musical scales, with the aim of enhancing our comprehension of the universality of music and the specificities of cultural expressions, thereby fostering intercultural understanding and respect. The study juxtaposes two distinct approaches: one grounded in the historical documentation and qualitative analysis of Yuan Dynasty court music; the other leveraging machine learning models for feature extraction and temporal categorization of musical samples. This paper scrutinizes the strengths and limitations of both methodologies, highlighting the capacity of historical musicology to deeply explore musical theories within particular cultural and historical contexts, and the computational musicology's ability to manage vast datasets, revealing the evolutionary patterns of musical scales over time. While the historical approach may lack extensive cross-cultural comparisons and quantitative analysis, and the computational method might not fully encapsulate the cultural and emotional facets of music, their integration offers novel perspectives and tools for musicological research. Future studies should strive to ensure the breadth and representativeness of data, continuously refining analytical algorithms to achieve a more holistic understanding of the complexities and dynamics of musical scales.

Xu Qinchen. Cross-Cultural and Computational Perspectives: A Comparative Study on Music Scale Perception and Interpretation. Frontiers in Art Research (2024) Vol. 6, Issue 7: 71-75. https://doi.org/10.25236/FAR.2024.060712.

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