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Showing 5 results for Bahri
Marzieh Ashouri, Hosein Bahri, Esmat Babaii,
Volume 24, Issue 1 (3-2021)
Abstract
Complexity of simultaneous interpreting has long attracted the interest of researchers and led them to explore different linguistic, psychological, cognitive, social, and neurological factors involved in enabling the human mind to perform such a difficult task. Within the framework of cognitive studies of interpreting, the authors of this study aimed at exploring the relationship between selective attention and interpreting performance of undergraduate students of Translation. Interpreting performance was evaluated in terms of content and presentation. A sample of 72 BA students participated in the study and completed a simultaneous interpreting and a selective attention task. Quantitative analysis of the data obtained from the participants led to the conclusion that selective attention had a direct relationship with both content and presentation of simultaneous interpreting performance in the sample as significant correlation was found to exist between the variables. The findings suggest that students with better selective attention are likely to perform better in interpreting tasks, especially in terms of the content of their performance which is concerned with completeness and accuracy of informational content of the interpreted message.
Aysa Arjmandpour, Hossein Bahri,
Volume 25, Issue 2 (9-2022)
Abstract
The novel Les Miserables (Hugo, 1985) is one of the most universally translated works, and there are a number of adaptions in several languages. One recent adaption is the Persian musical play performed in Iran. In this performance, culture-specific items (CSIs) were translated differently since visual and aural elements were added to the stage. The present study aims to investigate translation strategies used in the above adaptation to indicate what translation solutions are possible when the medium changes. After watching the ninety-minute recorded play in VOD format, culture-specific items were selected purposively corresponding to those in the novel. Subsequently, they were analyzed based on Newmark's model (1988). The findings showed that the most frequent translation strategies applied were adaptation, followed by communicative translation, and literal translation. Compared with the original performance, some scenes were deleted from the recorded play. Hence, there was no exact one-to-one correspondence with the original text of the book. While instances of censorship contributed to some of these omissions, probably one reason for the issue is the publishing regulations administered in Iran for VOD formats of the plays. These results suggest that while target language-oriented strategies dominated the entire translation approach, the translator of the play tried to familiarize the audience with French culture through literal translations and with the help of visual and aural aids. Since the audience were presented with pictures and songs, it was easier for them to locate themselves in the era of the French Revolution and French customs.
Simin Karimi , Hossein Bahri,
Volume 26, Issue 2 (9-2023)
Abstract
This study explores translators’ (in)visibility in translating English teen and young adult novels into Persian through various analytical perspectives. Five contemporary award-winning young adult novels were chosen for analysis. The textual aspect involved assessing the translator's influence using Baker’s translation universals: explicitation, simplification, and normalization. A sample of 300 sentences was scrutinized. The results indicated that translators utilized translation universals in 193 sentences, demonstrating considerable visibility. Four translators favored explicitation, while one preferred simplification, with normalization being the least prevalent strategy. The semiotic analysis of novel covers aimed to reveal the translators’ visibility. Utilizing Kress and Van Leeuwen’s (2006) framework, it was found that four covers featured smaller font sizes for translators’ names compared to the authors’, reflecting a diminished valuation of translators. None of the back covers acknowledged the translators, while authors’ names and images appeared on two, and publisher names were present on all five volumes. The paratextual analysis focused on the translators' presence in prefaces, postfaces, and footnotes. Three novels were devoid of both a preface and a postface. Translator acknowledgment was absent in the two novels with a postface, rendering them invisible. However, all five novels included footnotes, highlighting the translators' contributions and ensuring their visibility in this aspect. In conclusion, this study underscores the varying degrees of translators’ (in)visibility across different perspectives, particularly highlighting their underrepresentation in semiotic and paratextual domains.
Ms. Faezeh Moteshaker, Dr. Hossein Bahri,
Volume 27, Issue 2 (9-2024)
Abstract
This study investigates syntactic and thematic strategies by a translation model based on artificial intelligence, ChatGPT, in English to Persian literary translation. Mona Baker's (2011) theory of linear dislocation aims to assess whether and to what extent four major strategies (voice change, verb change, nominalization, and extraposition) occur in AI-generated text. The data set includes Thomas Hardy's short story Absent Mindedness in a Parish Choir and its full Persian translation produced by ChatGPT. A qualitative comparative method was adopted, in which Baker's scheme was taken as the starting point for text analysis. Forty four segments were identified and examined, each demonstrating the use of at least one of the mentioned strategies. The findings show that ChatGPT makes considerable use of all four strategies implicitly: verb change (31.82%), voice change (27.27%), nominalization (22.73%), and extraposition (18.18%). These results preserved thematic structure and communicative coherence in most cases. The study identifies ChatGPT's capacity to respond to functional translation in literary translation with idiomatic, rhythmic, and rhetorical fidelity. It suggests Baker's strategies are still relevant not only for human translators but also as a valuable instrument for evaluating and post-editing AI translations, especially literature. This study investigates syntactic and thematic strategies by a translation model based on artificial intelligence, ChatGPT, in English to Persian literary translation. Mona Baker's (2011) theory of linear dislocation aims to assess whether and to what extent four major strategies (voice change, verb change, nominalization, and extraposition) occur in AI-generated text. The data set includes Thomas Hardy's short story Absent Mindedness in a Parish Choir and its full Persian translation produced by ChatGPT. A qualitative comparative method was adopted, in which Baker's scheme was taken as the starting point for text analysis. Forty four segments were identified and examined, each demonstrating the use of at least one of the mentioned strategies. The findings show that ChatGPT makes considerable use of all four strategies implicitly: verb change (31.82%), voice change (27.27%), nominalization (22.73%), and extraposition (18.18%). These results preserved thematic structure and communicative coherence in most cases. The study identifies ChatGPT's capacity to respond to functional translation in literary translation with idiomatic, rhythmic, and rhetorical fidelity. It suggests Baker's strategies are still relevant not only for human translators but also as a valuable instrument for evaluating and post-editing AI translations, especially literature.
Ms. Zahra Vahdati, Dr. Hossein Bahri,
Volume 28, Issue 2 (9-2025)
Abstract
This study explores the challenges of translating humor and cultural references in the Persian subtitles of The Golden Girls, Season 5, Episode 24. The primary objective is to identify and analyze the translation strategies used in semiprofessional Persian subtitles and to compare them with AI-generated translations, to determine whether the loss of comedic tone, dilution of culture-specific elements, and difficulty conveying sarcasm persist or manifest differently within subtitling constraints when using AI tools. The analysis reveals common human strategies like adaptation, omission, and domestication used to address these challenges. Our findings indicate that while AI translations may achieve greater literal accuracy and consistency, they often exhibit a more pronounced failure in replicating comedic timing, recognizing nuanced sarcasm, and making contextually appropriate cultural substitutions, instead defaulting to overly literal or culturally neutral renderings that further diminish the source text's humor and cultural specificity. The paper proposes solutions, including cultural adaptation, creative clarification, and hybrid human-AI workflows to improve viewer understanding. The findings underscore the critical balance between staying faithful to the source and ensuring accessibility for the target audience in audiovisual translation, highlighting the continued irreplaceable role of human cultural and comedic intuition.
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