Automated speech translation, long a dream, has come into widespread use, as enterprises, application developers, and government agencies have become aware. Real-world S2ST applications have been tested locally over the past decade in consumer, healthcare, military, and humanitarian missions, and several projects aim to enable automatic cross-language communications at the 2020 Olympic Games to be held in Tokyo. Accordingly, this chapter provides a survey of the field’s technologies, approaches, companies, projects, and target use cases. (It is based on an industry report sponsored by the Translation Automation Users Society, released in 2017.) Sections examine the Past, Present, and Future of speech-to-speech translation. The first provides an orientation concerning issues in speech translation and a capsule history; the second snapshots technical achievements and representative participants in the burgeoning current scene; and the third speculates about future directions, with emphasis on platforms and form factors, big data, knowledge source integration, and the roles of human and automatic translators.

This chapter raises and addresses the key question of the relation between empirical translation studies and the descriptive branch of pure translation research initially proposed in the late 1980s. It analyses, explains, and illustrates the rationale and viability of the proposed ‘empirical turn’ in translation studies, which is to better align the central aims and purposes of the discipline with new, practical research needs arisen from our changing social environments in many parts of the world. It is argued in the conclusion that as demonstrated by the diverse chapters in the book, translation studies, especially the descriptive, empirical research branch has benefited and will continue to benefit from the integration of advanced quantitative research methodologies and advances in corpus analytical software development and natural language processing technologies such as machine translation. This bourgeoning translation research field is thus well equipped to play a larger, more significant role in addressing practical, pressing social and research issues such as environment communication, sustainable development and health literacy which is proposed as the much-needed ‘social turn’ in empirical translation studies.

We report the development of a multilingual system for the semantic analysis of text. The research on the English Semantic Tagger started in 1990, and after that the system has been ported, first, to Finnish and Russian, and, thereafter, to Arabic, Chinese, Czech, Dutch, French, Italian, Malay, Portuguese, Spanish, Urdu, and Welsh. The development processes of the semantic taggers for English, Finnish, and Russian were relatively similar, involving manual construction of the semantic lexicons, whereas, to speed up the research, new bootstrapping methods including computational approaches have been utilised later in the creation of the semantic lexicons for the other languages. We describe these manual and automatic processes as well as envisaging directions for future development. The resulting multilingual framework of semantic taggers based on equivalent semantic lexicons and one common semantic taxonomy offers a wealth of potential applications which this chapter also illustrates. In addition to developing monolingual applications for these semantic taggers, it is also possible to create cross-lingual and multilingual applications. Furthermore, while the existing semantic analysis systems are designed for the analysis of general language, such systems can also be tailored for a specific purpose to deal more accurately with only one particular domain or task.

This chapter provides an overview of the development of empirical translation studies as a rapidly growing and diversified field of Translation Studies since the 1980s. It examines the evolving identify of empirical translation studies in the last four decades, its changing research aims and priorities, as well as the experimentation with and development of corpus research methodologies which underscore the rapid growth of the field.

English and Japanese have very different word order and form one of the most difficult language pairs for translating each other. In statistical machine translation, it is well known that the translation accuracy between distant languages such as English and Japanese, is significantly lower than that between similar languages such as English and French. In this article, we describe a series of works done at our research groups in NTT to solve the problems in statistical machine translation between language pairs with very different word order such as Japanese and English.

This chapter offers an original study of the translation and circulation of the World Health Organisation Drinking Water Quality Guidelines (DWQG) (Third Edition) first published in 2004 by the Japanese Water Works Association. The translation of the principles and the suggestions put forward by authoritative, international health organisations in national contexts requires not only high quality translations, but also relies on the existence of an effective society-wide transmission network able to link together the main sources of information: governmental agencies, industrial and business sources, on the one hand, and the end users of the information distributed, on the other, that is, a wide range of industrial sectors associated with water. Using quantitative corpus linguistic methods and political discourse analysis frameworks, this study identifies and constructs a formalised empirical model of the social dissemination and adaptation of translated international drinking water health guidelines in Japan. This study illustrates, through the use of structural equation modelling, firstly, the main sources of information in Japan that drive and facilitate the distribution of translated health concepts, standards and regulatory approaches originally suggested in the WHO document; secondly, the mediating effect of the mass media, especially newspapers and magazines, on the transmission of translated information to industrial sectors; and thirdly, the differences in the attribution by direct and mediating sources of information of social accountability among industrial sectors in regard to the materialisation of four key aspects of the WHO drinking water quality guidelines: targets, standards, approaches, and actions.

Health translation readability assessment represents an important yet largely underexplored research area in translation studies. This chapter introduces an integrated analytical system developed for the computer-aided assessment of the readability of Chinese health translations. The system comprises two components which are a computerised Chinese text lexical profile analyser; and a data-driven statistical instrument that can be used to diagnose and label the readability level of Chinese translations and non-translated health education materials. The online Chinese lexical profile analyser was informed by recent research in corpus linguistics and Chinese educational literacy. It includes thirty-nine individual and compound lexical features to enable in-depth and systematic analyses of the lexical complexity and textual coherence of Chinese health education and promotion materials. The statistical instrument was developed using a large Australian Chinese Health Translation Corpus. The statistical instrument built contains two measurement scales which are related to the information load and the lexical technicality as two important indicators of the readability of Chinese health education resources. The study demonstrated the viability and effectiveness of developing digital analytical tools and instruments for the objective assessment of the readability of health materials, especially health translations which hold the key to the success and sustainability of health promotion and communication in multicultural societies with diverse population groups.

Technologies have transformed the way we work, and this is also applicable to the translation industry. In the past thirty to thirty-five years, professional translators have experienced an increased technification of their work. Barely thirty years ago, a professional translator would not have received a translation assignment attached to an e-mail or via an FTP and yet, for the younger generation of professional translators, receiving an assignment by electronic means is the only reality they know. In addition, as pointed out in several works such as Folaron (2010) and Kenny (2011), professional translators now have a myriad of tools available to use in the translation process.

John Searle and other influential theorists have argued that machine translation (MT) and other natural language processing (NLP) programs can never appreciate meaning in the deepest sense – in other words, that they can never truly exhibit semantics. It is true that MT and many other NLP systems have made steady and impressive progress while use of explicit semantic processing has undergone a rise and fall. It is also true that consensus among researchers on the meaning of meaning has remained elusive. In this chapter, however, we observe renewed interest in semantic representation and processing. Moreover, we foresee gradual adoption of semantic approaches grounded upon audio, visual, or other sensor-based input. We distinguish such perceptually-grounded semantic approaches from most current methods, which have tended to remain perception-free. With respect to philosophical implications, we suggest that perceptually-grounded approaches to automatic natural language processing can display intentionality, and thus foster a truly meaningful semantics. As background for these predictions and suggestions, we survey the role of semantics in machine translation to date in terms of three paradigms: rule-based, statistical, and neural MT. A section on each paradigm discusses its treatment of semantics: rule-based methods have generally emphasized symbolic semantics; statistical methods have generally avoided semantic treatment or employed vector-based semantics; and neural methods have handled meaning as implicit within networks.

Thanks to their ubiquitous presence in today’s society and their arresting nature, audiovisual productions have become the quintessential expression of multimodal communication in the 21st century. Video materials are a constant occurrence in an ever increasingly interconnected world, in which translation has become imperative in order to foster global communication across different languages and cultures. Interest in audiovisual translation (AVT) as a proper object of academic inquiry has been growing steadily and exponentially for the last three decades. This paper starts with a discussion of the main developments that, propitiated by technology, are shaping the new digital mediascape and propelling AVT to take centre stage. After exploring the multimodal specificities that set audiovisual material apart from other types of texts, an overview of the main translation modes is offered. The paper then moves to the focal point of this contribution, namely a discussion on the main conceptual, thematic and methodological perspectives that best characterise the research conducted in this domain.

Translation is a demanding, competitive, and labour-intensive activity that requires more than just advanced language skills. If translators are to thrive in such a cutting-edge working environment, they need to possess good computer literacy skills and be well-versed in the art of strategic information mining - in other words, they need to know how to make best use of the plethora of dictionaries, glossaries, books, websites, and other online resources at their disposal in order to find the required information in the shortest amount of time possible. This includes finding translation equivalents and domain-specific terms, checking collocations, idioms, and phrasal verbs, and exploring the way words are used in context by native speakers in order to render the text grammatically, semantically, and stylistically appropriate. Corpora, i.e. large electronic collections of computer-processed, linguistically annotated texts, can serve as an invaluable source of linguistic information, providing the translator with a sample of genuine texts in the target language and, in some cases, translations of similar texts. Over the past two decades, a wide variety of monolingual, comparable, and parallel corpora have been compiled, and these can be searched using either downloadable or online corpus query systems (CQS) such as the Sketch Engine. Whilst computer-assisted translation (CAT) tools such as SDL Trados and MemoQ are a staple of the translation process, translators are still relatively conservative when it comes to using corpora and CQSs to inform their practice. This chapter will introduce the Sketch Engine as a powerful suite of corpus tools for translation and cross-linguistic analysis. Centred around a case study featuring a real-life translation scenario, it will discuss various features of the software which can be used to leverage very large web-based monolingual and parallel corpora for translation, i.e. the concordancer, the word sketches tool, the thesaurus, the term extraction feature, and the corpus building tool.

Introduction

It is only relatively recently that scholars and the public have become aware of the accelerating loss of linguistic diversity around the world; consequently, the develop-ment of organised planning for survival in response to the crisis is also relatively new. Given that language planning for linguistic diversity is such a new endeavour, it is not surprising that a culture of professionalism and expertise among its practitioners is also still in the early stages of development. We have much to learn about what does and does not work when it comes to language planning in this respect, and there is also much work to be done in terms of disseminating this knowledge to those language planners, educators and activists working on the ground in indigenous communi-ties who might use it. This chapter explores the levels of training experienced and required by individuals involved in the implementation of planning interventions in the Scottish Gaelic context.

Background

In Scotland, the development of an organised, national response to the demographic decline of Gaelic-speaking communities is very recent indeed (see, for example, Dunbar 2010 and Macleod 2008). In the last quarter of the twentieth century, as language activists became increasingly concerned about the growing crisis in Gaelic-speaking communities, various initiatives in education, in the media, and in local-government service provision, were effected aiming to re-strengthen the transmission and use of Gaelic. These early efforts, while motivated by good intentions, were nonetheless characterised by a general lack of professional expertise. In the absence of a clear understanding of the nature of the problem, and without access to state-of-the-art theory of best practice in indigenous-language education and revitalisation, these early efforts tended to be of limited efficacy (McLeod 2002). Commenting in 2001, McLeod identified a lack of professionalisation in Scottish language planning bodies as a pervasive problem:

Under what conditions can an endangered minority language community offer hope and a vision to its members and a programme of action that is acceptable to its fellow majoritarian citizens? This is one of the most challenging of questions in any pluralist democracy, for so much of a minority's ambition is predicated upon the majority's rec-ognition of its right to exist and, if valued, to flourish. From contemporary Catalan, to Nahuati and Yucatec Maya to Maori, the fate of minoritised languages could be taken as a temperature gauge of a society's approach to cultural diversity and the worth of human dignity.

This volume represents a very welcome synthesis of our current understanding of the social context of Gaelic. Based in large part on the research undertaken by the Soillse network it represents the current state of the art with respect to the multiple dimensions of Gaelic, but the issues raised are indicative of wider, global trajec-tories. How the contributors approach their topics and together provide evidence-based policy recommendations thus has resonance far beyond the shores of Scotland. However, we acknowledge that there are many, often contradictory or ambiguous types of evidence, so much so that decision-makers tend either to be wary of such data or select those which fit their ideological predispositions as to the role of Gaelic in society.

This innovative volume is replete with scholarly analyses, insights, critical judge-ments and pragmatic observations. The fundamental questions asked refer to mean-ings and relevance, for the speakers and their neighbours, local authorities and national political representatives. As indicated in the introductory chapter the civil society platform upon which recent language revitalisation efforts have been constructed is relatively fragmented, deeply scarred and politically rather marginal. Questions of low social prestige, the hegemonic power of English and the political rhetoric of successive Scottish administrations still act as barriers to Gaelic being considered as a universal public good in society. Thus, it is critical that newer language affiliations and practices not only provide meaning-seeking experiences but also offer a robust defence for the promotion, protection and regulation of Gaelic.

Several interlinking methodologies and threads are given substantive, empirical life in the constituent chapters. Linguistic ideologies and authority are interpreted in settings as diverse as Edinburgh schools or within the NHS Eileanan Siar Gaelic language plan.