Echoes Across Centuries: Phonetic Signatures of Persian Poets

2026-03-15

AI Summary

This study investigates whether phonetic texture in classical Persian poetry constitutes a literary-historical phenomenon that transcends metrical constraints. Drawing on a corpus of over one million verse lines by 83 poets, the research establishes the first large-scale analytical framework that simultaneously accounts for metrical structure and individual stylistic variation. Controlling for five principal metrical patterns, the analysis integrates computational phonetic metrics—including phoneme transcription, consonant hardness, sonority, sibilance, vowel ratio, phonemic entropy, and consonant cluster density. Through multivariate statistical modeling and historical contextualization, the study uncovers systematic phonetic differences among poets, identifying distinct vocal profiles such as high-sonority lyrical, hard-consonant rhetorical, sibilant mystical, and high-entropy complex types, and demonstrates their evolution across centuries in relation to genre conventions, institutional frameworks, and performance contexts.

Technology Category

• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Application Domains: Humanities & Computational Social Science

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success

Abstract

This study examines phonetic texture in Persian poetry as a literary-historical phenomenon rather than a by-product of meter or a feature used only for classification. The analysis draws on a large corpus of 1,116,306 mesras from 31,988 poems written by 83 poets, restricted to five major classical meters to enable controlled comparison. Each line is converted into a grapheme-to-phoneme representation and analyzed using six phonetic metrics: hardness, sonority, sibilance, vowel ratio, phoneme entropy, and consonant-cluster ratio. Statistical models estimate poet-level differences while controlling for meter, poetic form, and line length. The results show that although meter and form explain a substantial portion of phonetic variation, they do not eliminate systematic differences between poets. Persian poetic sound therefore appears as conditioned variation within shared prosodic structures rather than as either purely individual style or simple metrical residue. A multidimensional stylistic map reveals several recurrent phonetic profiles, including high-sonority lyric styles, hardness-driven rhetorical or epic styles, sibilant mystical contours, and high-entropy complex textures. Historical analysis indicates that phonetic distributions shift across centuries, reflecting changes in genre prominence, literary institutions, and performance contexts rather than abrupt stylistic breaks. The study establishes a corpus-scale framework for phonetic analysis in Persian poetry and demonstrates how computational phonetics can contribute to literary-historical interpretation while remaining attentive to the formal structures that shape Persian verse.

Problem

• Persian poetry
• phonetic texture
• poetic style
• meter
• literary history

Innovation

• computational phonetics
• phonetic texture
• controlled corpus analysis
• stylistic profiling
• metrical conditioning