Through the lens of this research, I highlight the tendency towards oversimplification in representations of East Asian musical traditions, emphasizing a prevalent lack of exposure among contemporary musi- cians to the rich and diverse heritage of ancient East Asian music. My work seeks to bridge the chasm between traditional and contempo- rary musical practices, aiming to enhance understanding and appreci- ation of this particular musical heritage.

Central to this endeavor is a model designed to generate melodic continuations rooted in the "Baban" form, accompanied by a compre- hensive analysis of pieces created using this model. The implementa- tion of Computer Aided Composition in this context demonstrates its potential to illuminate the complexities of ancient East Asian music, thereby underscoring its cultural significance and educational value. Moreover, the research delves into the integration of Artificial Intelligence technologies, such as deep learning and neural networks, into the study and practice of traditional East Asian music.

By harnessing these advanced computational techniques, this study not only contributes to the creation of innovative compositions grounded in traditional theoretical frameworks but also encourages a reevaluation of how contemporary musicians engage with and reinterpret ancient musical forms. Ultimately, this research aspires to cultivate a deeper appreciation for the intricate tapestry of EastAsian musical heritage, fostering a dialogue between the past and the present in the realm of musical composition. 

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