讲座1 王华树博士

讲座题目:

大数据时代的翻译技术发展与翻译技术能力培养

Translation Technology in the Age of Big Data: Development and Training

内容提要:

In the age of Big Data, language services are of great demand A large number of translation tasks, for instance, game localization and post editing, can not be completed without modern translation technology.This talk aims to explore possible solutions on how to cultivate competent translators with up-to-date technology so as to meet the needs of the translation market. In this talk, the speaker firstly provides a global picture of the current development of translation technology, and then analyzes current problems in translator training in the context of translation technology. In closing, comprehensive abilities required for a competent translator are discussed.

    

在大数据时代,语言服务呈现出海量化、多元化、碎片化、多模态、即时性等特点,诸如游戏本地化、手机应用本地化、多媒体本地化、译后编辑等业务类型不断拓展,必须借助现代翻译技术来完成任务。在此需求推动之下,翻译和本地化技术发展迅猛,出现了整合化、智能化、众包化、流程化、云端化的发展趋势。例如,谷歌采用神经网络机器翻译(NMT)技术大幅提升机器翻译的水平,《麻省理工学院技术评论》杂志MIT TR 报道称之“几乎与人类无异”,神经网络机器翻译迅速成为世界关注的焦点,推动全球机器翻译研发热潮;以科大讯飞为代表的语音科技企业开发了语音听写、语音输入法、语音翻译、语音学习、会议听写、舆情监控等智能化语言技术;以SDL为代表的翻译工具开发商纷纷开发出基于网络的技术写作、翻译记忆、术语管理、语音识别、自动化质量保证、翻译管理等工具,并广泛应用于产业翻译实践之中。计算机辅助翻译软件从单机版走向网络协作、走向云端,从单一的PC平台走向多元化的智能终端。诸如Flitto、TryCan、Onesky等生态整合性的众包翻译平台也受益于大数据技术,蒸蒸日上。

语言技术的飞速发展,对翻译手段、翻译方式、翻译流程、翻译环境、翻译质量等都产生了巨大的影响,对语言服务人才的种类和能力提出了新的需求,对人才的翻译技术能力的要求越来越高。本次讲座将探讨在新的时代背景下,翻译技术发展趋势,分析翻译技术能力的演变以及翻译专业教育现存的问题,探讨如何培养学生的翻译技术能力,如何规划和实施翻译技术课程体系,如何培养翻译行业需求的具备综合技术能力的语言服务人才。

 

王华树博士简介:

王华树,翻译学博士,副教授,广东外语外贸大学高级翻译学院翻译技术教育与研究中心主任,世界翻译教育联盟(WITTA)翻译技术研究会会长,中国翻译协会本地化服务委员会副秘书长。

王华树博士曾任北京大学翻译硕士(MTI)教育中心翻译技术讲师,在Lionbridge、Symbio、IGS等国际化企业从事本地化工程、本地化测试以及本地化培训与咨询等工作。具有多年的翻译和本地化项目实战及教学经验。曾受邀到北外、上外、西外、北语、南开、复旦、同济、中大、辅仁大学、澳门大学等六十多所高校做翻译和本地化技术专题讲座,为三十多家企事业单位提供翻译和本地化技术培训及咨询。

在《中国翻译》、《外国语》、Journal of Translation Studies等学术期刊发表论文五十余篇。主持和参与十多项省部级科研课题。出版著作十多部,并参编多部翻译专著和教材。

 

讲座2 孙艺风博士

AI and Translation

Yifeng Sun

University of Macau

There has been much ill-informed and exaggerated talk about the prospect of artificial intelligence replacing human translation and interpreting. These widely circulated misconceptions are due largely to ignorance and lack of first-hand knowledge and extensive empirical analysis. There is no denying that, however, while simple and repetitive tasks of translation, such as weather forecast and other similar materials, can be and have already been more than adequately performed by machine translation, more sophisticated texts that are context dependent or sensitive and of an ambiguous, multilayered and polysemous nature, cannot be competently processed by AI translation. What about the future? If artificial intelligence eventually reshapes humanity, there is little doubt that AI translation will be very much part of the reshaping. It is probably beyond anyone's guess at this moment, when there is no way, as I shall demonstrate today (by citing some concrete examples), that AI translation can do a proper job, although it will certainly help facilitate translation practice.

About the speaker

Yifeng Sun is Chair Professor of Translation Studies and Head of the English Department at the University of Macau. He is formerly Dean of the Faculty of Arts and Director of the Centre for Humanities Research at Lingnan University, Hong Kong, and Honorary Professor and Distinguished Visiting Scholar at the University of Queensland, Australia. His publications include Translating Chinese Art and Modern Literature (London, 2018), Translating Foreign Otherness (London, 2017), Cultural Translation (Beijing, 2016), Translation and Academic Journals (New York, 2015), Translation, Globalisation and Localisation (Bristol, 2008), Perspective, Interpretation and Culture (Beijing, 2nd edition, 2006), Cultural Exile and Homeward Journey (Beijing, 2005), and Fragmentation and Dramatic Moments (New York, 2002). ​