The Linguist is a languages magazine for professional linguists, translators, interpreters, language professionals, language teachers, trainers, students and academics with articles on translation, interpreting, business, government, technology
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10 The Linguist Vol/55 No/6 2016 www.ciol.org.uk FEATURES In a shortened version of her Threlford Memorial Lecture, Dorothy Kenny asks what implications new technology has for the translation profession T ranslation without technology is now inconceivable, but the relationship between the two has become somewhat fraught of late. Even as translation activity continues to grow at a dizzying pace worldwide, translators worry about competition from computers, or having to work with poor quality machine output. At the same time, translation teachers are asking themselves what students should be learning now to see them safely through the 'revolutionary upheaval' currently under way in translation. After all, received wisdom is that education is the means by which human labour wins the race against technology. In coming to terms with current upheavals, there is no doubt that what we need is careful, critical examination of what is actually happening in the contemporary world of translation, one that avoids what Michael Cronin dubs "the dual dangers of terminal pessimism and besotted optimism". 1 These positions are all too present in current reflections on translation technology. Cyber- utopian visions of a world without language barriers abound, and even within translation studies, some commentators predict that machine translation will turn most translators into post-editors sometime soon. 2 Nor are predictions of wholesale automation limited to translation of the written word, where tools like Google Translate have already made their popular mark. If anything, technology pundits get even more excited about automatic translation of the spoken word – the very stuff of sci-fi fantasy. There are already several systems that use speech recognition to convert speech to written text in the same language, and then use conventional machine translation to translate that written text into another language. 3 All that's then needed is a speech synthesis module to speak the target-language text and we have speech- to-speech translation. The first two steps are error-prone and synthesising natural speech is challenging, but developers at one New York start-up are so confident that they can make the technology work that their Babel fish-style earpieces can already be pre-ordered. 4 Predicting the future Predictions about translation technology need careful scrutiny, because what we believe about the future has profound consequences for the decisions we make today. If it is only a matter of time before technology makes human translators and interpreters obsolete, or before post-editing displaces translation, should we still put effort into training translators and interpreters? And what might a career in post-editing look like anyway? What kind of conditions would post-editors work under? And would they like their jobs? Before pursuing these questions, I would like to stress that, while I support a critical approach to translation technology, I am not advocating an antagonistic approach. Despite frequent allusions to translators' supposed hostility to 'technology', there is little to suggest that they harbour negative sentiments towards technology per se. In one recent study by the Finnish researchers Kaisa Koskinen and Minna Ruokonen, for example, some 100 participants were invited to write a short love letter or break-up letter to a technological tool or some other aspect of their work. Most chose to write a love letter. 5 Koskinen and Ruokonen's study covers all sorts of technologies, from search engines to ergonomic mice, but the technologies that are most associated with translation are undoubtedly translation memory (TM) and machine translation (MT), and in particular, statistical machine translation (SMT). TM tools have been around since the 1990s. Put very simply, they store sentences from previously translated source texts alongside their human translations. If a source sentence (or something like it) is repeated in a subsequent translation job, the tool simply retrieves the existing translation for that sentence from memory and presents it to the human user, who can choose to accept, reject or edit it for current purposes. The human translator remains in control. Contemporary SMT, on the other hand, is fully automatic translation in which a computer program decides on the most probable translation for a given source sentence, based on a probabilistic model of translation that it has learned from pre-existing source texts and their human translations, The translator and THE MACHINE