The ethics of machine translation

In this paper I first describe the two main branches in machine translation research. I then go to discuss why the second of these, statistical machine translation, can cause some malaise among translation scholars. As some of the issues that arise are ethical in nature, I stop to ponder what an ethics of machine translation might involve, before considering the ethical stance adopted by some of the main protagonists in the development and popularisation of statistical machine translation, and in the teaching of translation

Teaching machine translation and translation technology: a contrastive study

The Machine Translation course at Dublin City University is taught to undergraduate students in Applied Computational Linguistics, while Computer-Assisted Translation is taught on two translator-training programmes, one undergraduate and one postgraduate. Given the differing backgrounds of these sets of students, the course material, methods of teaching and assessment all differ. We report here on our experiences of teaching these courses over a number of years, which we hope will be of interest to lecturers of similar existing courses, as well as providing a reference point for others who may be considering the introduction of such material

Technoneutral? university stances on contemporary translation technology

Much contemporary thought on technology in general, and translation technology in particular, is characterized by defeatism, determinism and a tendency towards universalism. The inexorable march of machine translation, we’re told, will turn us all into post-editors, while crowdsourcing will erode the professional basis of translation. But such comment does not pay enough attention to local differences, or the demands of specific languages and markets, and often little attempt is made to critique the practices that accompany technologization from a legal or ethical point of view. In this paper I consider how University programmes can help student translators prepare for a profession in which translation technologies may pervade, by helping them to develop not just technical skills, but also a high-level conceptual understanding of the technologies in question, and the critical ability that they will need to sustain careers in translation. My paper reviews a number of different translation studies responses to the challenges posed by technologization and especially by the rise of statistical machine translation (SMT). It draws on experience over the past four years of integrating SMT into the translation technology syllabus at Dublin City University, Ireland. It argues for a holistic treatment of technologies like SMT, one that involves translators at all stages of the translation workflow, and that takes account of the contexts in which technologies such as SMT are developed are applied

Taking statistical machine translation to the student translator

Despite the growth of statistical machine translation (SMT) research and development in recent years, it remains somewhat out of reach for the translation community where programming expertise and knowledge of statistics tend not to be commonplace. While the concept of SMT is relatively straightforward, its implementation in functioning systems remains difficult for most, regardless of expertise. More recently, however, developments such as SmartMATE have emerged which aim to assist users in creating their own customized SMT systems and thus reduce the learning curve associated with SMT. In addition to commercial uses, translator training stands to benefit from such increased levels of inclusion and access to state-of-the-art approaches to MT. In this paper we draw on experience in developing and evaluating a new syllabus in SMT for a cohort of post-graduate student translators: we identify several issues encountered in the introduction of student translators to SMT, and report on data derived from repeated measures questionnaires that aim to capture data on students’ self-efficacy in the use of SMT. Overall, results show that participants report significant increases in their levels of confidence and knowledge of MT in general, and of SMT in particular. Additional benefits – such as increased technical competence and confidence – and future refinements are also discussed

Selecting and preparing texts for machine translation pre-editing and writing for a global audience

Neural machine translation (NMT) is providing more and more fluent translations with fewer errors than previous technologies. Consequently, NMT is becoming a real tool for speeding up translation in many language pairs. However, obtaining the best raw MT output possible in each of the target languages and making texts suitable for each of the target audiences depends not only on the quality of the MT system but also on the appropriateness of the source text. This chapter deals with the concept of pre-editing, the editing of source texts to make them more suitable for both machine translation and a global target audienc

A STUDY OF GENDER IN SENIOR CIVIL SERVICE POSITIONS IN IRELAND. ESRI RESEARCH SERIES NUMBER 66 DECEMBER 2017

Women make up the majority of those employed in the civil service but are underrepresented at the most senior grades, where key policy and operational decisions are taken. Action 8 of the Civil Service Renewal Plan commits to improving gender balance at each level, including senior grades. The present study was commissioned by a high-level steering group set up to oversee implementation of this action. It draws on a combination of administrative data, reanalysis of the Civil Service Employee Engagement Survey conducted in 2015, and in-depth work history interviews with 50 senior civil servants across four departments. In addition, in-depth interviews were conducted with staff involved in recruitment and promotion within the public service. This rich combination of data yields new insights into the processes shaping gender differences in representation at the most senior grades of the civil service and thus provides a strong evidence base to inform future policy and practice

Sustaining Disruption? : On the Transition from Statistical to Neural Machine Translation

If statistical machine translation (SMT) was a disruptive technology, then neural machine translation (NMT) is probably a sustaining technology, continuing on a trajectory already established by SMT, and initially evaluated in much the same way as its predecessor. Seeing NMT in this light may be a useful corrective to the hype that has surrounded its introduction.Si la traducció automàtica estadística (TAE) va ser una tecnologia disruptiva, la traducció automàtica neuronal (TAN) probablement és una innovació incremental, que continua una trajectòria establerta per la TAE i que inicialment s'ha avaluat en gran part igual que la seva predecessora. Mirar la TAN des d'aquest punt de vista pot ser útil per matisar el bombo que envolta el seu sorgiment.Si la traducción automática estadística (TAE) fue una tecnología disruptiva, la traducción automática neuronal (TAN) probablemente es una innovación sostenida, que sigue una trayectoria establecida por la TAE y que inicialmente se ha evaluado en gran parte igual que su predecesora. Mirar la TAN desde este punto de vista puede ser útil para matizar el bombo que rodea su nacimiento

RISK TAKING AND ACCIDENTS ON IRISH FARMS: AN ANALYSIS OF THE 2013 HEALTH AND SAFETY AUTHORITY SURVEY. ESRI RESEARCH SERIES NUMBER 60 MAY 2017

The agricultural, fishing and forestry sector in Ireland has the highest rate of both fatal and non-fatal work-related injuries compared to other sectors (Health and Safety Authority (HSA), 2016). The HSA commissioned a 2013 nationwide research study to examine farm safety issues. That study involved a postal survey of farmers selected at random from the HSA database of farms, with a small booster sample of questionnaires completed by face-to-face interview at marts. Findings were presented in a report focusing on descriptive results regarding intentions to work safely, published in 2014 (HSA, 2014). The present study involves an in-depth analysis of the same survey data, but goes beyond the original report in calibrating the data to represent all farms and conducting detailed statistical analysis to identify the most important factors related to risk taking and how this is linked to accidents on farms

Mark my keywords: a translator-specific exploration of style in literary machine translation

This chapter presents a keyword analysis of a novel post-edited by the internationally acclaimed translator Hans-Christian Oeser. The novel, Christopher Isherwood's The World in the Evening, was first machine-translated into German using DeepL and then post-edited by Oeser. The analysis identifies words that are key in Oeser's post-edited text compared to the machine-translated version. It goes on to investigate whether these keywords are characteristic of Oeser's broader translation work and of German literary fiction in general. The chapter concludes that specific edits Oeser makes can be construed as an assertion of his translatorial style and hence constitute an instance of downstream translator-specific personalisation in literary machine translation

Machine translation for language learners

Machine Translation (MT) has been controversial in second and foreign language learning, but the strategic integration of MT might be beneficial to language learning in certain contexts. In this chapter we discuss the conditions in which MT can be useful in language learning, set out digital alternatives to MT, and provide examples of how MT can support language learners