A STUDY ON IDENTIFYING MAKAMS

Abstract

Makams are well-defined modes of classical Turkish music. They can be taken as the Turkish music counterparts of Western music tonal structures at a certain level. Nevertheless, makams have additional features such as the usage of specific notes resulting from their different architecture and the special use of scales (i.e. progression). The main goal of this study is to construct a platform for identifying makams through a computer program by proposing a machine learning mechanism. There are restrictions v on the mechanism related to the characteristics of the task. Such a mechanism should represent real-time sequential input with continuous values, should handle possible errors in this input and show immediate learning with limited data. These restrictions are valid and necessary for an analogy with the act of listening to music. A Boltzmann machine, modified for this purpose is designed, implemented and used in this study as this learning mechanism. Two characteristics of this study define its significance. First, this study is on the structural features of makams of classical Turkish music. Second, the identifying mechanism is a Boltzmann machine having a different schema than statistical identification tasks in tonality induction.