Implications of Arabic simile features in translation and transcreation of literary texts in the book of Al-’Abrat into English

The study of Arabic rhetorical characteristics, particularly similes, in translation has garnered significant interest due to their pivotal role in fostering intercultural understanding. Translating Arabic similes, known for their linguistic and cultural intricacies, poses significant challenges to translators. These challenges arise from the complex nature of similes, the use of implicit strategies, and subtle cultural nuances that affect meaning transmission across cultural boundaries. The aim of this research is to identify and analyse the translation problems encountered when translating Arabic similes present in “Al-’Abrat” by Mustafa Lutfi al-Manfaluti into English, with particular focus on linguistic and cultural nuances that hinder the translation process. In addition, Siddiqui’s main strategy for translating these Arabic similes is assessed, and the extent to which the translation favours a literal approach over a creative, transcreative strategy is determined. Furthermore, the study examines the impact of Arabic similes on the translation of literary texts, particularly in al-Manfaluti’s “Al- ’Abrat,” and explores the potential applications of advanced machine learning methods, such as natural language processing techniques, to analyse these similes and their translations. A Python-based program was employed to identify instances of similes in the translation of “Al-’Abrat” into “The Tears.” The researcher then carried out a manual verification process to confirm the accuracy of these findings, resulting in 200 verified similes that served as the data set for the study. Employing a descriptive and interpretive methodology, the study analysed these 200 pairs of similes and their translations from Arabic to English, taken from the story anthology “Al-’Abrat.” The findings indicate that the predominant strategy — retaining the original simile vehicle — was evident in 61% of cases, highlighting a preference for literal translation to preserve the original imagery of the simile while incorporating adaptive strategies for cultural relatability. The analysis reveals a higher prevalence of literal translation strategies compared to creative or transcreative approaches, indicating a departure from the dynamic and integrative translation practices recommended in the literature. This preference for literal interpretation underscores the difficulty of balancing linguistic accuracy with capturing cultural and emotional nuances in translation. The study also explores the potential of interdisciplinary approaches, including computational linguistics, to enhance translation precision and promote cross-cultural understanding. The application of natural language processing techniques offers new insights into the complex interplay of language, culture, and cognition in literary texts. This research makes a valuable contribution to the wider discussion of Arabic-English literary translation and emphasises the importance of a deep understanding of both cultural and linguistic elements in this process. Theoretical frameworks by Abdul-Raof (2006), Pierini (2007), Lakoff and Johnson (1980), and Ketola (2018) served as the basis for analysing translation difficulties, strategies, and the implications of rhetorical features. This integration of machine learning into literary translation research promises to open innovative ways of understanding and preserving the emotive and cultural dimensions of original works in their translated form.

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