Contour analysis of Hungarian folk music in a multidimensional metric-space

A collection of folk tunes of a Hungarian ethnic group was investigated usi ng a mathematical model, relating multi-dimensional points to melodies. The distribution of the points was studied using eigenvector analysis of the c orrelation matrix. A scalar measure of musical distance was formulated, in accord with the Euclidean norm, in the basis of the most important eigenvec tors. The analysis of the distances between the points indicated cluster fo rmation in agreement with the results of classical musicology. Visual repre sentation was accomplished by projecting the multi-dimensional space to a t wo dimensional plane of variable position.