Musical Scales Recognition via Deterministic Walk in a Graph

Abstract

Musical scales play an important role in melodies, since its properties are reflected to the melodic essence. The extraction and understanding of scales are essential in both analysis and composition of music. However, the scale identification is a nontrivial task. Consequently, classic algorithms for identifying scales have been developed based on the most popular scales, such as major and minor scales. In this paper, we propose a comprehensive method for identifying musical scales, which allows to detect a wide range of scales beyond the traditional ones. Our method uses a deterministic walk through the nodes of a graph, where each node represents a valid interval structure. The transition between nodes is performed following a validation rule that governs the fragmentation of intervals. Moreover, if the scale is incomplete, possible structures can be determined and the scale is estimated according to the harmonic similarity percentage measure. The proposed method has been tested using a database of Finnish folk melodies and a data set of random melodies composed using rarely used scales. Experimental results show good performance of the proposed technique.