Machine translation: Turkish-English bilingual speakers' accuracy detection of evidentiality and preference of MT.

IF 3.4 2区 心理学 Q1 PSYCHOLOGY, EXPERIMENTAL
Sümeyra Tosun
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Abstract

Machine translation (MT) is the automated process of translating text between different languages, encompassing a wide range of language pairs. This study focuses on non-professional bilingual speakers of Turkish and English, aiming to assess their ability to discern accuracy in machine translations and their preferences regarding MT. A particular emphasis is placed on the linguistically subtle yet semantically meaningful concept of evidentiality. In this experimental investigation, 36 Turkish-English bilinguals, comprising both early and late bilinguals, were presented with simple declarative sentences. These sentences varied in their evidential meaning, distinguishing between firsthand and non-firsthand evidence. The participants were then provided with MT of these sentences in both translation directions (Turkish to English and English to Turkish) and asked to identify the accuracy of these translations. Additionally, participants were queried about their preference for MT in four crucial domains: medical, legal, academic, and daily contexts. The findings of this study indicated that late bilinguals exhibited a superior ability to detect translation accuracy, particularly in the case of firsthand evidence translations, compared to their early bilingual counterparts. Concerning the preference for MT, age of acquisition and the accuracy detection of non-firsthand sentence translations emerged as significant predictors.

机器翻译:土耳其语-英语双语者对证据性的准确检测和对 MT 的偏好。
机器翻译(MT)是在不同语言之间翻译文本的自动化过程,涵盖了广泛的语言对。本研究以土耳其语和英语的非专业双语使用者为对象,旨在评估他们辨别机器翻译准确性的能力以及他们对 MT 的偏好。其中特别强调了证据性这一语言上微妙但语义上有意义的概念。在这项实验调查中,我们向 36 名土耳其语-英语双语者(包括早期和晚期双语者)展示了简单的陈述句。这些句子的证据意义各不相同,有第一手证据和非第一手证据之分。然后,向受试者提供这些句子的两种翻译方向(土耳其语译英语和英语译土耳其语)的 MT,并要求受试者辨别这些翻译的准确性。此外,还询问了参与者在医学、法律、学术和日常生活等四个关键领域对 MT 的偏好。研究结果表明,与早期双语者相比,晚期双语者在检测翻译准确性方面表现出更强的能力,尤其是在第一手证据翻译方面。关于对 MT 的偏好,学习年龄和非第一手句子翻译的准确性检测是重要的预测因素。
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
CiteScore
6.80
自引率
7.30%
发文量
96
审稿时长
25 weeks
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