Formation of a Unified Alphabet of Ancient Turkic Dialects for Image Annotation

Abstract

This paper is devoted to the development of a unified alphabet of Ancient Turkic dialects for solving the problems of automated recognition of Orkhon–Yenisei runic inscriptions. The relevance of the study is determined by the fragmentation of existing rune classifications and the absence of a unified system for correlating symbols across different sources and regions, which complicates the formation of compatible datasets and reduces the efficiency of computer vision models. The research is to create a unified alphabet that ensures correct image annotation and enables the training of multi alphabet neural network models for the recognition and comparative analysis of runic symbols. The methodology is based on a comprehensive analysis of visual, phonetic, and historical-philological characteristics of runes from four sources: the Kül Tegin monument, the Irk Bitig manuscript, Orkhon inscriptions, and Yenisei inscriptions. During the study, structurally stable symbols, stylistic variations, and unique dialect markers were identified, on the basis of which a consolidated set of rune classes was formed. The obtained results provide a foundation for the standardization of image annotation, improvement of recognition robustness, and further development of multi-alphabet computer vision systems in the study of Ancient Turkic writing.