Motive Identification in 22 Folksong Corpora Using Dynamic Time Warping and Self Organizing Maps

A system for automatic motive identification of large folksong corpora is described in this article. The method is based on a dynamic time warping algorithm determining inherent repeating elements of the melodies and a self-organizing map that learns the most typical motive contours. Using this system, the typical motive collections of 22 cultures in Eurasia have been determined, and another great common self organising map has been trained by the unified collection of the national/areal motive collections. The analysis of the overlaps of the national-areal excitations on the common map allowed us to draw a graph of connections, which shows two main distinct groups, according to the geographical distribution.