Prof Lynne Bowker, School of Translation & Interpretation, University of Ottawa

Machine translation literacy in the context of non-professional translation

18 December 2020

We recently passed the 70^th anniversary of Weaver’s Memorandum (1949), which is widely acknowledged as having launched machine translation (MT) research. A lot has happened in that 70-year period, including the introduction of free, online machine translation accessible to anyone with an internet connection. Through university-based translator education programs and professional development opportunities offered by professional translators associations, language professionals have numerous opportunities to learn more about how to interact effectively with MT tools. But these tools are no longer solely in the hands of language professionals; they are also “in the wild”. How and why are non-professional users employing MT? What do they need to be aware of to use it effectively? What support is available to non-professional users of MT? Why should developers care about non-professional users? In this talk, we will explore the notion of “machine translation literacy”, examine some of the needs of non-professional MT users, consider the social responsibility of translators toward non-professional users, and discuss the results of two different efforts to deliver MT literacy training to non-professional users (one as part of a workshop offered through a university library, and one as part of a first-year university course on translation for non-language professionals).

Bio-sketch

Lynne Bowker is a certified (French-English) translator and holds a PhD in Language Engineering from the University of Manchester Institute of Science and Technology (UK). She is Full Professor at the School of Translation and Interpretation at the University of Ottawa (Canada), with a cross-appointment to the School of Information Studies. She is the author of Computer-Aided Translation Technology (University of Ottawa Press, 2002) and co-author of both Working with Specialized Language: A Practical Guide to Using Corpora (Routledge, 2002) and Machine Translation and Global Research (Emerald, 2019). In 2020, she was elected to the Royal Society of Canada in recognition of her contributions to research in translation technologies.

Andrzej Zydroń, XTM International (CTO)

AI and Language Technology: De-demonizing AI

16 December 2020

AI gets a lot of attention generally due to the stunning results that can be achieved, in fields such as medicine, automotive technology, diagnostic systems and of course translation. AI systems can seemingly outperform human beings in a wide range of tasks, from playing Chess, Go or even poker, to face and voice recognition. What is often lacking though, is a more realistic understanding of what intelligence is and the actual limitations that exist given the computing tools at our disposal.

The reality is much more prosaic: most of the mathematical basis of what is termed AI is not complicated and generally rooted in early 18^th century mathematics, namely work done by Euler and Bayes.

Although some of the achievements of AI based systems may seem phenomenal, they are achieved through processing of gigantic amounts of data which would normally be beyond human capability. The presentation looks at what actually constitutes AI and how it relates to general human intelligence and what implications this has for the translation industry in general.

Andrzej Zydroń MBCS CITP

CTO and co-founder @ XTM International, Andrzej Zydroń is one of the leading IT experts on Localization and related Open Standards. Zydroń sits/has sat on the following Open Standard Technical Committees:

1. LISA OSCAR GMX
2. LISA OSCAR xml:tm
3. LISA OSCAR TBX
4. W3C ITS
5. OASIS XLIFF
6. OASIS Translation Web Services
7. OASIS DITA Translation
8. OASIS OAXAL
9. ETSI LIS
10.  DITA Localization
11. Interoperability Now!
12. Linport

Zydroń has been responsible for the architecture of the essential word and character count GMX-V (Global Information Management Metrics eXchange) standard, as well as the revolutionary xml:tm standard which will change the way in which we view and use translation memory. Zydroń is also head of the OASIS OAXAL (Open Architecture for XML Authoring and Localization technical committee.

Zydroń has worked in IT since 1976 and has been responsible for major successful projects at Xerox, SDL, Oxford University Press, Ford of Europe, DocZone and Lingo24.

Diana Ballard, STAR Group

Scaling language technologies to overcome growing challenges and deliver new value

11 December 2020

To tackle growing complexity, volumes, languages, channels, media how are language technologies shaping up to meet today’s challenges and what developments are on the horizon? In this session, we will explore the importance of workflow automation to blend the language technology ecosystem to tackle growing complexity, showcasing STAR challenges. Our example will focus on unlocking the value of Big Data to deliver reliable Translation Memory through a process of alignment and Machine Translation.

 CLM (Corporate Language Management). Secondly, we will discuss a real-world case where blending language technologies can answer new 

Bio:

Over 20 years, Diana has worked in international business development and global account management at Language Service Companies. Prior to this, she was technical communications manager at a Japanese Manufacturing company migrating its technical information operations from Japan to the UK where she supervised the end-to-end information process from authoring, translation, approval, printing and delivery to the assembly line. Previously, Diana gained early experience at a business development consultancy having graduated from the University of Liverpool, where she read English Literature and French.

Dr Antoni Oliver González, The Open University of Catalonia

Techniques for automatic terminology extraction: implementation into TBXTools

9 December 2020

In this talk main techniques for automatic terminology extraction and for automatic detection of translation equivalents of terms will be presented. The talk includes an explanation of the implementation of these techniques into TBXTools, a free tool for terminology extraction. We will explore statistical and linguistic methodologies for terminology extraction. We will also present the implementation of automatic search of translation equivalents of terms in parallel corpora and in statistical machine translation phrase tables.

Dr. Antoni Oliver

Antoni Oliver is a lecturer at the Universitat Oberta de Catalunya (UOC, Barcelona, Spain) and the director of the master’s degree in Translation and Technologies. His main areas of research are machine translation and automatic terminology extraction. He is developing TBXTools, a free terminology extraction tool, available at https://github.com/aoliverg/TBXTools

Prof William D Lewis, University of Washington and Microsoft Translator:

Automatic Speech Transcription and Translation in the Classroom and Lecture Setting: The Technologies, How They’re Being Used, and Where We’re Going        

4 December 2020

Abstract:

We have witnessed significant progress in Automated Speech Recognition (ASR) and Machine Translation (MT) in recent years, so much so that Speech Translation, itself a combination of these underlying technologies, is becoming a viable technology in its own right. Although not perfect, many have called what they’ve seen of the current technology the “Universal Translator” or the “mini-UN on a phone”. But we’re not done and there are many problems to solve. For example, for Speech Translation to work well, it is not sufficient to stitch together the two underlying technologies of ASR and MT and call it done. People are amazingly disfluent, which can have profound negative impacts on transcripts and translations. We need to make the output of ASR more “fluent”; this has the effect of improving the quality of downstream translations. Further, since “fluent” output is much more readable and “caption-like” than disfluent, it is also more easily consumable by same-language users. This opens doors to broader accessibility scenarios. Speech Translation is currently being used in a variety of scenarios, no more so than in education. It sees its greatest uptake in settings where one or more speakers needs to communicate with a multilingual population. Perfect examples are the classroom, but we also see its use in parent-teacher conferences. The underlying technologies can be enhanced further by giving users some control over customizing the underlying models, e.g., to domain-specific vocabulary or speaker accents, significantly improving user experiences. In this talk I will demonstrate the technology in action as part of the presentation.

Dr. William Lewis is an Affiliate Assistant Professor at the University of Washington, and until recently, a Principal PM Architect with the Microsoft Translator team.  He has led the Microsoft Translator team’s efforts to build Machine Translation engines for a variety of the world’s languages, including threatened and endangered languages, and has been working with the Translator team on Speech Translation.  He has been leading the efforts to support the features that allow students to use Microsoft Translator in the classroom, both for multilingual and deaf and hard of hearing audiences. 

Biography

Before joining Microsoft, Will was Assistant Professor and founding faculty for the Computational Linguistics Master’s Program at the University of Washington. Before that, he was faculty at CSU Fresno, where he helped found the Computational Linguistic and Cognitive Science Programs at the university. 

He received a Bachelor’s degree in Linguistics from the University of California Davis and a Master’s and Doctorate in Linguistics, with an emphasis in Computational Linguistics, from the University of Arizona in Tucson. In addition to regularly publishing in the fields of Natural Language Processing and Machine Translation, Will is on the editorial board for the Journal of Machine Translation, has previously served on the board for the Association for Machine Translation in the Americas (AMTA), served as a program chair for the National American Association for Computational Linguistics (NAACL) conference, served as a program chair for the Machine Translation Summit, regularly reviews papers for a number of Computational Linguistic conferences, and has served multiple times as a panelist for the National Science Foundation. 

Prof Stephen Doherty, University of New South Wales

Eye movements, cognitive load, and human-computer interaction with translation and interpreting technologies

2 December 2020

Technological advances have led to unprecedented changes to translation and interpreting (see Doherty, 2016), chiefly in how we access and use translation and interpreting technologies for a diverse and growing range of professional and personal activities. Previous empirical research on translation and interpreting technologies has yielded a wealth of evidence to advance our understanding and usage of these technologies in addition to making them more visible and accessible. Of particular value amongst this growing body of work is the use of eye tracking in exploring and understanding the psychological and cognitive aspects of translation and interpreting technologies by analysing our eye movements as we interact with these technologies and use their outputs.

In this paper, I will consolidate this work by presenting a critical review of empirical studies of translation and interpreting technologies which have employed eye tracking, including my own recent work in the Language Processing Lab at the University of New South Wales. I will categorise previous research into areas of application, namely: computer-assisted translation tools, quality assessment of machine translation, post-editing machine-translated output, audio-visual translation, and remote interpreting. In closing, I will discuss the strengths and limitations of eye tracking in such studies and outline current and future research.

Suggested background reading:

Doherty, S. (2016). The impact of translation technology on the process and product of translation. International Journal of Communication, 10, 947–969.

Speaker’s bio

I am Associate Professor in Linguistics, Interpreting, and Translation, and lead of the HAL Language Processing Research Lab at UNSW. With a focus on the psychology of language and technology, my research investigates human and machine language processing using natural language processing techniques and combinations of online and offline methods, mainly eye tracking and psychometrics. My research has been supported by the Australian Research Council, Science Foundation Ireland, the European Union, the Federal Bureau of Investigation, the National Accreditation Authority for Translators and Interpreters, New South Wales Ministry of Health, Enterprise Ireland, and a range of industry collaborations. As a Chief Investigator, I have a career total of $1.5 million competitive research grants. 

Prior to my appointment at UNSW Sydney (2014), my doctoral (2008–2012) and post-doctoral research positions (2012–2013) were funded by Science Foundation Ireland and supervised by Prof Sharon O’Brien, Prof Dorothy Kenny, and Prof Andy Way at the CNGL Centre for Global Intelligent Content in Dublin City University, a multi-million euro, cross-institutional centre now known as the ADAPT Centre for Digital Content Technology. My subsequent post-doctoral position (2013–2014), supervised by Prof Josef Van Genabith, was based in the School of Computing and the National Centre for Language Technology at Dublin City University as part of the QTLaunchPad project, a €2.2 million project funded by the European Union through its Seventh Framework Programme (FP7) for research and technological development.