A memory-based maximum entropy model has been developed to simulate the learning in an oral musical tradition, with the aim to find the optimal segment streams in melody sections. The model operated on a representative set of 2323 Hungarian folk songs. The pentatonic motive boundaries became more and more preferred during convergence, which shows the self-supporting feature of pentatonality in certain melodic systems. A pronounced correlation between typical segment contours and complete section contours poses the existence of certain typical schemata at macro-and micro levels in the melodies.
To find the essential musical relations characterising 2323 typical Hungarian folk melodies as a musical system, we developed a method relating melodies to points of a multidimensional Euclidean melody space. The study of the resulting point systems is based on the method of principal component analysis, and shows the inherent relations of a rich oral musical tradition as a very regular, unbroken clustered structure. The majority of the points are grouped in parallel as well as perpendicular clusters. The musical interpretation of parallelism and orthogonality highlights certain basic construction and variation principles in Hungarian folk music.
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