"Musiqi dünyası" Vol.28 № 2 (107) 2026

30.06.2026

Article №3; 43-68 pages.
Bağırov F., İsfəndiyarova T. Modal musiqinin funksional qarammatikası: modal təşkilatlanmanın vahid nəzəriyyəsinə doğru
Багиров Ф. Исфандиярова Т. Функциональная грамматика модальной музыки: на пути к единой теории модальной организации
Baghirov F., Isfandiyarova T. Functional grammar of modal music: towards a unified theory of modal organization

https://doi.org/10.65058/KODO1039

FUAD BAGHIROV
Ph.D in Technical science
Khazar University
E-mail: fuad.baghirov@khazar.org
https://orcid.org/0009-0000-7858-4593   

TURKAY ISFANDIYAROVA
Baku Music Academy
E-mail: tisfandiyarova@gmail.com
https://orcid.org/0009-0003-7471-6554

Bakı: Musiqi dünyası. Beynəlxalq Elmi
Musiqi Jurnalı, – 2026.Vol.28/№2 (107), s. 43-68.

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Keywords: Modal music, Functional Grammar, Music Information Retrieval, Computational Musicology, Melodic Trajectories, Generative Artificial Intelligence

Abstract
The present study proposes a theoretical framework for representing modal music through functional organization rather than solely through acoustic or statistical properties of pitch sequences. Despite substantial historical and cultural differences, Azerbaijani mugham, Turkish makam, Indian raga, and Gregorian chant exhibit functional analogies in the organization of melodic development around stable reference points, secondary centers, characteristic trajectories, and recurrent melodic structures. Existing Music Information Retrieval (MIR) approaches primarily operate on acoustic features, pitch distributions, or statistical regularities and may therefore remain limited in capturing higher-level functional logic. To address this gap, we introduce the Functional Grammar of Modal Music (FGMM), a generalized representation in which modal melodies are modeled as trajectories through a space of functional states constrained by stylistic rules and transition structures. FGMM identifies four minimal components: a primary functional center, a secondary functional center, a developmental trajectory, and recurrent melodic patterns. The framework is formulated independently of any single musical tradition and is intended to support structural analysis, automatic classification, cross-cultural comparison, and interpretable algorithmic generation. We further outline a computational pipeline and quantitative descriptors for future implementation. The study should be regarded as a conceptual and mathematical foundation for empirical validation rather than as a completed computational system. Its principal contribution is the identification of underexplored functional analogies between historically independent modal traditions and the proposal of a common representational language linking comparative musicology, MIR, and generative artificial intelligence.