一个心理不健康角色的言语形象翻译问题

IF 0.2 0 HUMANITIES, MULTIDISCIPLINARY Nauchnyi Dialog Pub Date : 2023-10-29 DOI:10.24224/2227-1295-2023-12-8-47-64
E. A. Barmina, O. G. Skidan
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引用次数: 0

摘要

本文的目的是描述在翻译中实现语用充分性方面确定文学文本中心理不健康角色的言语肖像的关键参数的机制。用于分析的材料包括丹尼尔·凯斯的小说《为阿尔杰农的花》、斯蒂芬·金的短篇小说《幸存者类型》、布雷特·伊斯顿·埃利斯的小说《美国精神病患者》。作者利用提出的预翻译分析算法作为工具。在文学文本中,通过一个或多个参数观察到特定的语言标记在创造言语肖像方面的作用。这些语言标记准确地表征了精神障碍患者语言意识改变的事实。人物言语画像的组成部分可能包括言语攻击(淫秽语言)、隐喻、特定的句子结构、夸张的语言化等。作者的结论是,该算法应用心理语言学数据,可以追踪原文中选择表达手段的特点,并识别出心理不健康角色的语音画像的相关标记,以便随后将这些特征表示为翻译中的功能优势。这样可以避免翻译过程中人物形象的转换。
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Speech Portrait of a Mentally Unhealthy Character as a Translation Problem
The aim of this article is to describe the mechanism of determining the key parameters of the speech portrait of a mentally unhealthy character in a literary text in terms of achieving pragmatic adequacy in translation. The material used for analysis includes the novel ‘Flowers for Algernon’ by Daniel Keyes, the short story ‘Survivor Type’ by Stephen King, and the novel ‘American Psycho’ by Bret Easton Ellis. The authors utilize a proposed algorithm of pretranslation analysis as a tool. It has been established that specific linguistic markers are employed in creating the speech portrait in literary texts, observed through one or multiple parameters. These linguistic markers accurately characterize the existing facts of altered language consciousness in mental disorders. Components of the character’s speech portrait may include verbal aggression (obscene language), metaphors, specific sentence structures, verbalization of grandiosity, etc. The authors conclude that the proposed algorithm, with the application of psycholinguistics data, allows for tracing the peculiarities of selecting expressive means in the original text and identifying relevant markers of the speech portrait of a mentally unhealthy character for subsequent representation of these characteristics as functional dominants in translation. This will help avoid shifts in realizing the character’s image in translation.
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Nauchnyi Dialog
Nauchnyi Dialog HUMANITIES, MULTIDISCIPLINARY-
CiteScore
0.10
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发文量
215
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