امیرمحمد گل

This study conducts a comprehensive computational stylometric analysis of Persian literary translations with the aim of identifying and investigating the distinctive stylistic features of each individual translator. By employing a quantitative corpus-based methodology, this study explores the ways in which translators' stylistic preferences manifest in translations, thus reconceptualizing translation as inherently a task that is always imbued with the qualities of the individual's style. The corpus of the study contains sixteen translated texts by four Iranian translators (Kiumars Parsai, Mahdi Afshar, Najaf Daryabandari and Nazi Azima), each contributing four works. The study uses Python and the Hazm natural language processing (NLP) toolkit to extract and analyze lexical, character, syntactic and semantic features. Additionally, the study utilizes three corpus similarity methods (Mendenhall's characteristic curves of composition, Kilgarriff's Chi-squared and Burrows' Delta) to measure stylistic consistency and variation within translations. The findings show that indeed, it is possible to observe translators’ style through recurrent linguistic patterns found within all four feature dimensions, while lexical features, specifically, word preferences demonstrate the greatest potential for differentiating stylistic identities. Of the translators studied, Kiumars Parsai displays the most distinct and consistently identifiable style. The study also recognizes Kilgarriff's Chi-Squared test as the most effective procedure for testing corpus-level similarity and highlights the impact that the source text genre can have on the translators' observable stylistic patterns. In addition to its contribution to empirical understanding, the study advances methodological practices utilizing corpus-based Translation Studies (CTS) by illustrating the applicability of stylometric tools to Persian texts, a language with limited computational stylistic resources. In this way, the study contributes to the knowledge of translator's style, while also providing a model for scholars interested in researching stylistic individuality in translation with computational tools.

Keywords: Stylometry, Translator’s Style, Computational Stylistics, Persian Literary Translation