The Effect of Translation on Text Coherence: A Quantitative Study

IF 0.7 2区文学 0 LANGUAGE & LINGUISTICS

Journal of Quantitative Linguistics Pub Date : 2020-06-16 DOI:10.1080/09296174.2020.1774297

Elham Najafi, Alireza Valizadeh, A. Darooneh, A. Darooneh

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引用次数: 2

Abstract

ABSTRACT Investigating the coherence of translated texts is an important issue in multilingual studies. In this paper, we aim to study text coherence in human translated texts and its relation to the text properties by a quantitative approach. For this purpose, we assigned a word importance value to each word-type of a text and construct the text ‘importance time series’ from the original and translated texts. Then, we calculated text global coherence by applying Detrended Fluctuation Analysis (DFA) to these time series. By means of this procedure, we were able to compare the coherence of the original and translated texts. Our results show that a translation does not always decrease text coherence, as many people may suppose; there are many cases where text coherence is increased by translation. We also studied the relation of text coherence and the text properties such as text size or vocabulary size; we observed no relevance. Our findings suggest that the coherence of a text depends on the translator’s abilities rather than the state of being original or translated.

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翻译对语篇连贯影响的定量研究

摘要研究翻译文本的连贯性是多语言研究中的一个重要问题。本文旨在用定量的方法研究人类翻译文本中的语篇连贯及其与文本性质的关系。为此，我们为文本的每个单词类型分配了一个单词重要性值，并从原始文本和翻译文本构建了文本“重要性时间序列”。然后，我们通过对这些时间序列进行去趋势波动分析(DFA)来计算文本的全局相干性。通过这种方法，我们可以比较原文和译文的连贯性。我们的研究结果表明，翻译并不总是像许多人想象的那样降低文本的连贯性;在许多情况下，通过翻译提高文本的连贯性。本文还研究了文本连贯与文本大小、词汇量等文本属性的关系;我们没有观察到相关性。我们的研究结果表明，文本的连贯取决于译者的能力，而不是原文或译文的状态。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Quantitative Linguistics Multiple-

CiteScore

2.90

自引率

7.10%

发文量

期刊介绍： The Journal of Quantitative Linguistics is an international forum for the publication and discussion of research on the quantitative characteristics of language and text in an exact mathematical form. This approach, which is of growing interest, opens up important and exciting theoretical perspectives, as well as solutions for a wide range of practical problems such as machine learning or statistical parsing, by introducing into linguistics the methods and models of advanced scientific disciplines such as the natural sciences, economics, and psychology.