The Routledge Handbook of Translation and Technology

Minako O'Hagan, Minako O'Hagan

• Publisher: Routledge
• Year: 2019
• ISBN:
  9781315311234
• Edition: 1
• Topic: Languages & Linguistics
• Subtopic: Linguistics
• Index: Languages & Linguistics

The Routledge Handbook of Translation and Technology provides a comprehensive and accessible overview of the dynamically evolving relationship between translation and technology.

Divided into five parts, with an editor's introduction, this volume presents the perspectives of users of translation technologies, and of researchers concerned with issues arising from the increasing interdependency between translation and technology. The chapters in this Handbook tackle the advent of technologization at both a technical and a philosophical level, based on industry practice and academic research.

Containing over 30 authoritative, cutting-edge chapters, this is an essential reference and resource for those studying and researching translation and technology. The volume will also be valuable for translators, computational linguists and developers of translation tools.

1

Introduction

Translation and technology: disruptive entanglement of human and machine

Minako O’Hagan

Background

This book builds on the increasing evidence of the impact of technology on contemporary translation, which serves diverse communicative situations across languages, cultures and modalities. The 2018 European Language Industry Association (ELIA) survey of over 1,200 respondents across 55 countries highlighted 2018 ‘as the year in which more than 50% of both the companies and the individual language professionals reported as using MT’ (ELIA 2018: n.p.). Although the ELIA report is cautious not to overstate the penetration of MT, concluding that the use of MT in the translation industry is not yet mainstream, it is clear that technology has already profoundly affected the way translation is produced. Similarly, the wider public is exposed to machine translated texts of varying quality in different scenarios, including user-generated content (e.g., social media postings) and information gisting for personal use (e.g., hotel reviews). Furthermore, portions of the increased production and circulation of translations are attributable to the work of fans, volunteers or activists who have different backgrounds and motivations, yet are operating in parallel to their professional counterparts. The increased visibility of non-professional translation (NPT) can be traced to the availability of technology-supported social and collaborative platforms, on which NPT typically operates (see Chapter 14 by Jiménez-Crespo). In this way, technology has contributed to translation of diverse types and quality, accompanied by an increasing awareness in society at large of translation and the role played by technologies in the translation process. More recently, the newest MT paradigm, neural MT (NMT) is making inroads into translation practice and adding to substantial research interests in Translation Studies (TS), as demonstrated in this volume. The influence of technology, ranging from translation-specific technologies such as MT to more general-purpose speech technologies and cloud computing, is far-reaching and calls into question some of the assumptions about who should translate, how and to what level of quality.

Commercially viable translation today is all computer-aided (or -assisted) translation (CAT) and has been for some time. This is a term which comes across as somewhat redundant, given the ubiquitous use of computers in text production practices in general, except that the extent and the nature of the computer aid is constantly shifting. Another frequently used term in the translation industry is translation environment tools (TEnTs), which conveys an image of translators’ work surroundings being enveloped by technology. Among the newer terms coming into use is augmented translation (AT), introduced by Common Sense Advisory (Lommel 2018). AT puts the human translator in the centre (Kenny 2018), supported by an advanced suite of technologies, including automated content enrichment (ACE). This allows automatic searches of relevant information associated with the source content and informs the translator and MT to generate better translation (Lommel ibid.). AT and ACE concepts align with AI-supported medicine, which augments human expert judgement with rapid access to vast and relevant key information (see Susskind and Susskind 2015). Such complex technological infrastructure shaping macro and micro translation environments in turn relies on ongoing behind-the-scenes standardization work (see Chapters 2 and 3 by Wright and Roturier respectively) to ensure that all technological elements meet required standards and can therefore interoperate. However, the technology-driven modus operandi and technology-based infrastructure on which translation increasingly rests adds to quality concerns (see Pym in Chapter 26). For example, according to nearly 2,800 respondents to the SDL Translation Technology Insight Survey (SDL 2016), quality is currently of the utmost concern for the translation industry.

These snapshots highlight that the human–machine relationship is in a state of flux, with uncharted paths ahead. While human translation shapes and is shaped by technologies, we do not know exactly how this process will unfold. This contributes to a sense of uncertainty among professional translators, which Vieira (2018), following Akst (2013), calls ‘automation anxiety’ (also see Kenny in Chapter 30). In the midst of ongoing technological transformation, this collected volume is not about translation technology per se. Rather, it is about understanding the dynamic relationship being formed between translation and technology from a range of perspectives. In doing so, it aims to increase our awareness of how contemporary translation is evolving and what it means to be a translator, as the co-existence of human and machine could be qualitatively different in the near future. Such a theme has become a major agenda of the 21st century across different types of work, particularly with AI beginning to affect areas previously considered only fit for humans (Susskind and Susskind 2015, also see Chapter 30 by Kenny). This volume attempts to tackle the topic both at a technical and a philosophical level, based on industry practice and academic research, to present a balanced perspective with TS contributions to a dialogue of global importance.

Historical contexts of research on the nexus of human and machine in translation

For translation, the explicit connection with ‘the machine’ started in earnest in the 1950s, with research and development (R&D) of MT as a new field for the non-numerical application of computers instigated by the Weaver memo (Weaver 1949) (see Melby in Chapter 25). However, as is well known, the 1966 Automatic Language Processing Advisory Committee (ALPAC) report put an abrupt end to MT R&D, especially in the US, for nearly a decade. Despite this, the frequent references to the ALPAC report in this volume and elsewhere are arguably evidence of its continuing legacy, which is perhaps not all short-sighted and misguided. For example, its support for ‘machine-aided translation’ has become mainstream in the translation industry under the banner of CAT. Martin Kay’s translator’s amanuensis (Kay 1980/1997) envisioned an incremental adaptive electronic aid for the human translator. Similarly, Alan K. Melby’s work on the translator’s workstation (Melby 1981) embodied a workbench integrating discrete levels of machine aid. Reviewing these pioneers’ concepts, Hutchins (1998: 11) highlighted how, in both cases, the human translator had been placed in control as someone who would use such tools in ways s/he ‘personally found most efficient’. The questioning of this centrality of human translators in today’s transforming translation workflow (Kenny 2018), further validates the aim of this volume to investigate the relationship between human and machine and its ramifications.

Initially CAT tended to be distinguished from MT on the assumption that in the former, it is the human who translates (e.g., Bowker 2002, Somers 2003), whereas MT is automatic computer translation without human intervention. However, this division has become blurred as MT is increasingly integrated into CAT environments (see Kenny in Chapter 30) where the human translator is presented with translation proposals from (human produced) translation memory (TM) matches, together with MT outputs. Similarly, the increasing practice of post-editing of MT (PEMT) is reflected in a growing body of research which has rapidly reached a critical mass especially in translation process research (see collected volumes such as O’Brien 2014, Carl, Bangalore and Schaeffer 2016).

There has been considerable progress made to address the earlier disconnect between MT research and research in TS, although the tendency to exclude professional human translators is still observable ‘in certain quarters of MT research’ (Kenny 2018: 439). Initially MT research focused on the application of computers to human language, with computer scientists and engineers ‘knowingly or unknowingly’ attempting to ‘simplify the translation process’ or ‘downplay the nuances of human language’ (Giammarresi and Lapalme 2016: 218). But the lack of cross-fertilization can also be blamed on the TS camp, with too few scholars interested in translation technology to widen the scope of translation theory, so that it could consider the increasing integration of technology into the translation process (O’Hagan 2013, Jakobsen and Misa-Lao 2017). In fact, the connection between translation research and MT research can be traced to the 1960s when the idea of equivalence relationships between source and target texts was explored by linguists such as Catford (1965). In particular, Catford’s idea of a translation rule as ‘an extrapolation of the probability values of textual translation equivalents’ (1965: 31) is of direct relevance to subsequent data-driven approaches to MT (Kenny forthcoming), which are based on the use of parallel texts (or bi-texts) (see Simard in Chapter 5). In the 1960s, when Chomsky’s linguistic theory (Generative Grammar) was exerting its influence, including on MT, Eugene Nida was among the few early translation theorists cognizant of MT research, and related to it in his foundation work Toward a Science of Translating (Nida 1964). In his endeavour to bring theorizing about translation into the scientific arena, Nida applied Chomskian linguistics and the information theory approach to communication (Nida 1964, Nida and Taber 1969). It is relevant to recall the fact that MT R&D precede the development of TS; it was only in 1972 that James Holmes (1972/1988) named the discipline as ‘Translation Studies’ (abbreviated as TS in this article) and laid the foundations for theorizing translation to ‘explain and predict’ translation with ‘description’ as the first step. In the 1980s TS was shifting away from a linguistic focus to a consideration of broader contexts through functionalism. Attention moved from the source to the target text and translation as action, before the cultural turn in the 1990s moved human translation largely outside the scope of interest of MT circles.

Into the 1990s and 2000s technologies played a key role in empirical TS research by providing research tools, including some for corpus analysis. Other tools, such as keyboard logging (e.g., Translog originally developed by Arnt Jakobsen at the Copenhagen Business School in the late 1990s) and eye tracking (see Jakobsen in Chapter 24), were also introduced more widely into TS, and these have been used to better understand translator behaviours and the behaviours of translation users in the context of translation reception; for example, in audiovisual translation (AVT) (see Kruger 2018). In particular, these research tools contributed to the further development of cognitive translation studies as a specialized field of research (see Schwieter and Ferreira 2017), one which is now set to probe neural representation with non-invasive neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) (see Shreve and Diamond 2016: 155).

This brief look back at the trajectory of the connection between translation and technology shows increasing ‘border crossings’ (Gambier and van Doorslaer 2016) to neighbouring disciplines such as computer science, computational linguistics and now neuroscience.

Aim and scope of the publication

The spread of computers across global markets gave rise to new areas of practice and research in TS, such as localization (see Folaron in Chapter 12). This saw TS scholars engaging more fully in theorizing about technologies by tapping into sociological, cultural or philosophical aspects (see Chapters 23 and 31 by Olohan and Cronin respectively), on the one hand, and cognitive or usability/ergonomic dimensions on the other (see Chapters 21 and 24 by Ehrensberger-Dow and Murphy; and Jakobsen respectively). There is also a large body of knowledge being accumulated in translator training and education focused on technology (see Kenny in Chapter 30). Furthermore, as a result of technological advances, research-led practices are becoming more common in fields such as accessibility and universal design (see Remael and Reviers in Chapter 29). In this way, technology more than anything else started to bring together the interests of academy and industry. Technological dimensions continue to present fresh scope to bridge the gap between translation theory and practice, ideally to respond to ever-present translator suspicions as to the usefulness of theory in actual translation practice – a topic earlier addressed in Chesterman and Wagner (2002) and more recently in Polizzotti (2018). As demonstrated in this volume, the exploration of the relationship between technology and translation is leading to a fresh examination of contemporary translation benefitting not only translators as users of technologies but also those who develop and research translation technology. It is hoped that this volume contributes critical insight into the complex symbiosis between humans and machines so that translation (and interpreting, which is covered to a limited extent in this volume) can serve increasingly diverse communication needs in the best and most sustainable way.

With the above overall goal of the publication, the Handbook has a number of specific features. First, it is designed to represent the interests of different stakeholders in the translation industry. The fragmented nature of the translation industry is recognized as it affects the level of implementation and the types of technologies used in translation. The translation industry consists of a large population of freelance translators (see Zetzsche in Chapter 10) and language service providers (LSPs) which range from small-and-medium-sized (see King in Chapter 9) to multinational vendors (see Esselink in Chapter 7). In addition, often well-resourced public international organizations (see Caffrey and Valentini in Chapter 8) play an important role as early adopters of new technologies. Although not officially part of the industry, non-professional translation is also contributing to translation production, forming part of a participatory culture (Chapters 13 and 14 by Altice and Jiménez-Crespo, respectively). Similarly, the use of translation technology in (second) language learning is part of the picture in the technology and translation alliance (see Chapter 11 by Yamada). The volume therefore reflects different settings for technology uses according to the different segments of the industry as users of translation technology, encompassing contributors who reside outside academia. Secondly, this publication attempts to make sense of the current position of technology from diachronic perspectives. What is considered new technology often had a prior incarnation as a rudimentary prototype or an embryonic concept which needed further maturing, perhaps requiring relevant surrounding technologies and conditions. While historical approaches are well explored in TS research in general, their application in the context of translation technology research has not been traversed to the same extent. In the context of MT, John Hutchins was the first to demonstrate the merit of a historical approach with his comprehensively chronicled Machine Translation: past, present, future (Hutchins 1986). The Routledge Encyclopedia of Translation Technology (Chan 2015) is a more recent example also with regional foci. Among the many chapters in the present volume which provide a historical trajectory, historical perspectives are more applicable and prominent in certain chapters. For example, Sue-Ellen Wright in her chapter on Standards follows periodization, drawing on Galinski (2004 cited in Wright) to cast a spotlight on key phases of the evolution of approaches and applications of standardization across language, translation and the localization industry. Similarly, Debbie Folaron (Chapter 12), in discussing technical translation as an established practice and localization as a relatively new addition within TS, traces their historical trajectories. The historical approach contexualizes and recontextualizes the development of specialized translation practices in dynamic interaction with technology. Such an approach allows Folaron to present a critical discourse on the links between technology and localization as well as technical translation, enabling the author to systematize the epistemology of the field. In turn, Sabine Braun (see Chapter 16 on technology and interpreting) tracks technological developments in telecommunications which have shaped varied modes of distance interpreting and configurations of technical settings. This richly traces the new demands on professional interpreters to serve different technological constructs as their working environments. Thirdly, this volume addresses a number of substantive matters under Part V as overarching issues that challenge translation practice and research concerned with technology, ranging from quality to ecology. This part, along with the research foci and methodologies addressed in Part IV, aims to provide scholars and industry players with key topics, fu...

Table of contents

• Cover
• Half-Title Page
• Series Page
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• List of Figures
• List of Contributors
• Acknowledgements
• 1 Introduction: Translation and technology: disruptive entanglement of human and machine
• Part I Translation and technology: defining underlying technology – present and future
• 2 Standards for the language, translation and localization industry
• 3 XML for translation technology
• 4 Terminology extraction and management
• 5 Building and using parallel text for translation
• 6 Speech recognition and synthesis technologies in the translation workflow
• Part II Translation and technology: users’ perspectives
• 7 Multinational language service provider as user
• 8 Applications of technology in the Patent Cooperation Treaty (PCT) Translation Division of the World Intellectual Property Organization (WIPO)
• 9 Small and medium-sized enterprise (SME) translation service provider as technology user: Translation in New Zealand
• 10 Freelance translators’ perspectives:
• 11 Language learners and non-professional translators as users
• Part III Translation and technology: application in a specific context – shaping practice
• 12 Technology, technical translation and localization
• 13 Technology and game localization: Translation behind the screens
• 14 Technology and non-professional translation
• 15 Technological advances in audiovisual translation
• 16 Technology and interpreting
• 17 Technology and sign language interpreting
• 18 Translation technology and disaster management
• 19 Post-editing of machine translation
• Part IV Translation and technology: research foci and methodologies
• 20 Translation technology evaluation research
• 21 Translation workplace-based research
• 22 Translation technology research and human–computer interaction (HCI)
• 23 Sociological approaches to translation technology
• 24 Translation technology research with eye tracking
• Part V Translation and technology: overarching issues
• 25 Future of machine translation: Musings on Weaver’s memo
• 26 Quality
• 27 Fit-for-purpose translation
• 28 Copyright and the re-use of translation as data
• 29 Media accessibility and accessible design
• 30 Technology and translator training
• 31 Translation, technology and climate change
• Index