Department of Translation and Interpreting

ADDRESS
Department of Translation and Interpreting
Humanities and Social Sciences Building (HSS Building), South Campus
Xi'an Jiaotong-Liverpool University
8 Chongwen Road Suzhou Dushu Lake Science and Education Innovation District , Suzhou Industrial Park
Suzhou,Jiangsu Province,P. R. China,215123
1. Framing international news in China: An analysis of trans-edited news in Chinese newspapers

Author:Kuang, XW;Wang, H

Source:GLOBAL MEDIA AND CHINA,2020,Vol.5

Abstract:This research explores the variations between Chinese party and non-party newspapers in the framing of trans-edited international news. Existing studies on the framing of Chinese domestic news show that the variations depend on the sensitivity of news, which invokes government control. However, it is not clear how strictly the government would control international news and whether party and non-party news organizations would show similarities or variations in the framing of it. To address these issues, we conducted a comparative quantitative content analysis of 806 pieces of trans-edited international news from one party newspaper and one non-party newspaper. The findings show that the party and non-party newspapers show similarity on the use of three frames but small variations on the other four. This implies a strong control of the Chinese government on the reporting of international news. By comparison, the government control has stronger effects on the party newspaper than on its non-party counterpart.
2. Corpora for document-level neural machine translation

Author:Liu,Siyou;Zhang,Xiaojun

Source:LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings,2020,Vol.

Abstract:Instead of translating sentences in isolation, document-level machine translation aims to capture discourse dependencies across sentences by considering a document as a whole. In recent years, there have been more interests in modelling larger context for the state-of-the-art neural machine translation (NMT). Although various document-level NMT models have shown significant improvements, there nonetheless exist three main problems: 1) compared with sentence-level translation tasks, the data for training robust document-level models are relatively low-resourced; 2) experiments in previous work are conducted on their own datasets which vary in size, domain and language; 3) proposed approaches are implemented on distinct NMT architectures such as recurrent neural networks (RNNs) and self-attention networks (SANs). In this paper, we aim to alleviate the low-resource and under-universality problems for document-level NMT. First, we collect a large number of existing document-level corpora, which covers 7 language pairs and 6 domains. In order to address resource sparsity, we construct a novel document parallel corpus in Chinese-Portuguese, which is a non-English-centred and low-resourced language pair. Besides, we implement and evaluate the commonly-cited document-level method on top of the advanced Transformer model with universal settings. Finally, we not only demonstrate the effectiveness and universality of document-level NMT, but also release the preprocessed data, source code and trained models for comparison and reproducibility.
3. Feasibility and acceptability of in-depth annotated parallel corpus-aided translation teaching

Author:Wang,Hui

Source:Handbook of Research on Teaching Methods in Language Translation and Interpretation,2014,Vol.

Abstract:© 2015 by IGI Global. All rights reserved. This chapter probes into the feasibility and acceptability of integrating an in-depth annotated parallel corpus into the translation classroom. It proceeds from outlining the conceptual and structural features of English/Chinese Online Translation Teaching Platform, an in-depth annotated parallel corpus designed for teaching and (self-) learning of translation. With a 90-minute lecture as a demo, it illustrates how the combined unity of course teaching materials and the platform, as well as the teaching method and the annotation mode of the corpus, can be effectively achieved. It then discusses users' perceptions of the use of the platform in classroom teaching as shown in a recent survey and points out the possibilities of future development.
4. How Do Subalterns Represent Themselves?——Study of the Narratives about"Labor"by Female Workers and Farmers on Women of New China

Author:LIU Xi;WANG Hui

Source:Journal of China Women's University,2017,Vol.29

Abstract:This paper studies the self-narrationof women' s liberation by women workers and peasants published on Women o~New China in early period of the People's Republic of China. It argues that these narratives are influenced by the state-sanctioned conceptual and discursive framework, but not identical to them. Women authors interrogate socialist political and gender discourses in the discursive construction of their past experiences. They creatively employ the new cultural category of "labor" to valorize their past productive practice and economic contribution. It is in the complex, dynamic process of self-representation that their subjectivities are constituted, their bottom agency created and asserted.
5. “精加工”平行语料库在翻译教学中的应用

Author:王惠

Source:Chinese Translators Journal,2015,Vol.36

Abstract:本文探讨如何将手工标注的"精加工"平行语料库与教学细节有效结合,以辅助翻译教学。在课程教学目标的指引下,语料库可以作为教学内容的有机组成部分参与教学过程;语料库中的习题及答案设计,与利用语料库设计的课后练习相配合,对于加深和巩固知识点的理解和掌握大有裨益。语料库中的"学习历史"和"练习成绩"栏还可以帮助教师随时了解学习者的学习状况,以设定下一个教学步骤。
6. Seven Principles to Construct the Reliable Machine Translation System

Author:ZHANG Xiaojun;SHAO Lu

Source:Journal of Sichuan International Studies University,2021,Vol.37

Abstract:人工智能和机器翻译的工程伦理是对人工智能和机器翻译产品或者系统设计和研发过程中所涉及的道德价值、问题和决策的研究。本文分析工程伦理学在人工智能产品和机器翻译系统研发过程中的主要问题,并在美国谷歌公司和欧盟委员会先后发布的人工智能的技术伦理准则基础上总结了实现可信赖的机器翻译系统的七个基本原则。这七个原则基本涵盖了机器翻译产品和系统在设计与研发过程中所涉及的主要工程伦理问题,同时也认为,"人工翻译能否被机器翻译所取代"这样的问题需要厘清机器翻译的工程伦理问题之后才能展开全面、系统的讨论。
7. 基于工程伦理的机器翻译系统基本原则

Author:张霄军;邵璐

Source:中国社会科学文摘,2021,Vol.

Abstract:对于机器翻译研发者而言,机器翻译系统的开发与应用是一项系统工程,任何未经检验的论断都会涉及人工智能和机器翻译技术的工程伦理问题。目前讨论人工翻译能否被“取代”为时尚早,我们应该尽快厘清的是机器翻译的工程伦理问题。
8. Multiword Units in Machine Translation and Translation Technology

Author:Wang, H;Zhang, XJ

Source:BABEL-REVUE INTERNATIONALE DE LA TRADUCTION-INTERNATIONAL JOURNAL OF TRANSLATION,2019,Vol.65

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