Translation and Interpreting as a Profession: Some Proposals to Boost Entrepreneurial Competence

Increasing automation and the emergence of new needs and forms of communication are triggering a redefinition of the role and work settings of translators and interpreters. For this reason, and with a view to enhancing employability, students need to be aware of the range of professional profiles they can pursue and the value they can bring to society. The aim of this paper is to put forward a series of teaching proposals aimed at promoting entrepreneurial competence. After presenting the results of an exploratory study of students’ views of the profession, it proposes some activities that are considered particularly useful for fostering entrepreneurial competences.&nbsp

Language technologies for a multilingual Europe

This volume of the series “Translation and Multilingual Natural Language Processing” includes most of the papers presented at the Workshop “Language Technology for a Multilingual Europe”, held at the University of Hamburg on September 27, 2011 in the framework of the conference GSCL 2011 with the topic “Multilingual Resources and Multilingual Applications”, along with several additional contributions. In addition to an overview article on Machine Translation and two contributions on the European initiatives META-NET and Multilingual Web, the volume includes six full research articles. Our intention with this workshop was to bring together various groups concerned with the umbrella topics of multilingualism and language technology, especially multilingual technologies. This encompassed, on the one hand, representatives from research and development in the field of language technologies, and, on the other hand, users from diverse areas such as, among others, industry, administration and funding agencies. The Workshop “Language Technology for a Multilingual Europe” was co-organised by the two GSCL working groups “Text Technology” and “Machine Translation” (http://gscl.info) as well as by META-NET (http://www.meta-net.eu)

Findings of the 2019 Conference on Machine Translation (WMT19)

This paper presents the results of the premier shared task organized alongside the Conference on Machine Translation (WMT) 2019. Participants were asked to build machine translation systems for any of 18 language pairs, to be evaluated on a test set of news stories. The main metric for this task is human judgment of translation quality. The task was also opened up to additional test suites to probe specific aspects of translation

Proceedings of the 17th Annual Conference of the European Association for Machine Translation

Proceedings of the 17th Annual Conference of the European Association for Machine Translation (EAMT

Language technologies for a multilingual Europe

This volume of the series “Translation and Multilingual Natural Language Processing” includes most of the papers presented at the Workshop “Language Technology for a Multilingual Europe”, held at the University of Hamburg on September 27, 2011 in the framework of the conference GSCL 2011 with the topic “Multilingual Resources and Multilingual Applications”, along with several additional contributions. In addition to an overview article on Machine Translation and two contributions on the European initiatives META-NET and Multilingual Web, the volume includes six full research articles. Our intention with this workshop was to bring together various groups concerned with the umbrella topics of multilingualism and language technology, especially multilingual technologies. This encompassed, on the one hand, representatives from research and development in the field of language technologies, and, on the other hand, users from diverse areas such as, among others, industry, administration and funding agencies. The Workshop “Language Technology for a Multilingual Europe” was co-organised by the two GSCL working groups “Text Technology” and “Machine Translation” (http://gscl.info) as well as by META-NET (http://www.meta-net.eu)

Development of an international written communication audit

Although localization, internationalization, and globalization efforts to meet international customers\u27 product and information needs are accepted strategies in the US computer industry, the needs of second language (L2) English speakers are less directly addressed in the international workplace. Application of strategies similar to these three technical communication strategies may benefit international workplace communication;The international writing approaches represented by these three communication strategies are related to the global management strategies of organizations (e.g., ethnocentric, polycentric, geocentric). This categorization, based on Perlmutter and Hedlund, considers organizations\u27 strategic missions and can be used to align management strategies with international writing approaches and individual rhetorical strategies. For example, an ethnocentric organization, entering the international market from a broad national base, instead of immediately changing its communication approach, might continue to use its source-localized information to communicate internationally. An organization might enter the global arena with an ethnocentric strategy, and, in reaction to emerging problems, focus on localization for each market and rely heavily on translation and translators, becoming more polycentric in its approach. A geocentric organization, balancing between ethnocentric and polycentric management strategies, is in constant communication across national and language borders, and might use both internationalization and globalization approaches in communication. Organizations\u27 global management strategies should align with their international communication practices, both for customers and in the workplace. An organization seeking a larger role in international ventures, yet with ethnocentric, localized communication strategies, might be less successful than one with similar goals and a more geocentric, globalized communication;In recognition of the diverse needs of organizations and individuals, an assessment method, an International Written Communication Audit (IWCA), is developed in this dissertation. The IWCA, based on linguistic and contrastive rhetoric research, focuses on cultural, pragmatic, and translation issues important to international workplace writing in US-English. The basic IWCA combines internationalization and globalization approaches. A localization module for the PRC is offered as an example of tailoring the audit methodology to the needs of L2 English readers from a specific language group. The construction of a workplace sampling frame and the analysis of the IWCA data are discussed

Empirical studies in translation and discourse (Volume 14)

The present volume seeks to contribute some studies to the subfield of Empirical Translation Studies and thus aid in extending its reach within the field of translation studies and thus in making our discipline more rigorous and fostering a reproducible research culture. The Translation in Transition conference series, across its editions in Copenhagen (2013), Germersheim (2015) and Ghent (2017), has been a major meeting point for scholars working with these aims in mind, and the conference in Barcelona (2019) has continued this tradition of expanding the sub-field of empirical translation studies to other paradigms within translation studies. This book is a collection of selected papers presented at that fourth Translation in Transition conference, held at the Universitat Pompeu Fabra in Barcelona on 19–20 September 2019

Moving Boundaries in Translation Studies

Translation is in motion. Both translation practice and translation studies (TS) have seen considerable innovation in recent decades, and we are currently witnessing a wealth of new approaches and concepts, some of which refect new translation phenomena, whereas others mirror new scholarly foci. Volunteer translation, crowdsourcing, virtual translator networks, transediting, and translanguaging are only some examples of practices and notions that are emerging on the scene alongside a renewed focus on well-established concepts that have traditionally been considered peripheral to the practice and study of translation: intralingual and intersemiotic translation are cases in point. At the same time, technological innovation and global developments such as the spread of English as a lingua franca are affecting wide areas of translation and, with it, translation studies. These trends are currently pushing or even crossing our traditional understandings of translation (studies) and its boundaries. The question is: how to deal with these developments? Some areas of the translation profession seem to respond by widening its borders, adding new practices such as technical writing, localisation, transcreation, or post-editing to their job portfolios, whereas others seem to be closing ranks. The same trend can be observed in the academic discipline: some branches of translation studies are eager to embrace all new developments under the TS umbrella, whereas others tend to dismiss (some of) them as irrelevant or as merely refecting new names for age-old practices. Translation is in motion. Technological developments, digitalisation and globalisation are among the many factors affecting and changing translation and, with it, translation studies. Moving Boundaries in Translation Studies offers a bird’s-eye view of recent developments and discusses their implications for the boundaries of the discipline. With 15 chapters written by leading translation scholars from around the world, the book analyses new translation phenomena, new practices and tools, new forms of organisation, new concepts and names as well as new scholarly approaches and methods. This is key reading for scholars, researchers and advanced students of translation and interpreting studies. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 licens

Deep Neural Networks for Automatic Speech-To-Speech Translation of Open Educational Resources

[ES] En los últimos años, el aprendizaje profundo ha cambiado significativamente el panorama en diversas áreas del campo de la inteligencia artificial, entre las que se incluyen la visión por computador, el procesamiento del lenguaje natural, robótica o teoría de juegos. En particular, el sorprendente éxito del aprendizaje profundo en múltiples aplicaciones del campo del procesamiento del lenguaje natural tales como el reconocimiento automático del habla (ASR), la traducción automática (MT) o la síntesis de voz (TTS), ha supuesto una mejora drástica en la precisión de estos sistemas, extendiendo así su implantación a un mayor rango de aplicaciones en la vida real. En este momento, es evidente que las tecnologías de reconocimiento automático del habla y traducción automática pueden ser empleadas para producir, de forma efectiva, subtítulos multilingües de alta calidad de contenidos audiovisuales. Esto es particularmente cierto en el contexto de los vídeos educativos, donde las condiciones acústicas son normalmente favorables para los sistemas de ASR y el discurso está gramaticalmente bien formado. Sin embargo, en el caso de TTS, aunque los sistemas basados en redes neuronales han demostrado ser capaces de sintetizar voz de un realismo y calidad sin precedentes, todavía debe comprobarse si esta tecnología está lo suficientemente madura como para mejorar la accesibilidad y la participación en el aprendizaje en línea. Además, existen diversas tareas en el campo de la síntesis de voz que todavía suponen un reto, como la clonación de voz inter-lingüe, la síntesis incremental o la adaptación zero-shot a nuevos locutores. Esta tesis aborda la mejora de las prestaciones de los sistemas actuales de síntesis de voz basados en redes neuronales, así como la extensión de su aplicación en diversos escenarios, en el contexto de mejorar la accesibilidad en el aprendizaje en línea. En este sentido, este trabajo presta especial atención a la adaptación a nuevos locutores y a la clonación de voz inter-lingüe, ya que los textos a sintetizar se corresponden, en este caso, a traducciones de intervenciones originalmente en otro idioma.[CA] Durant aquests darrers anys, l'aprenentatge profund ha canviat significativament el panorama en diverses àrees del camp de la intel·ligència artificial, entre les quals s'inclouen la visió per computador, el processament del llenguatge natural, robòtica o la teoria de jocs. En particular, el sorprenent èxit de l'aprenentatge profund en múltiples aplicacions del camp del processament del llenguatge natural, com ara el reconeixement automàtic de la parla (ASR), la traducció automàtica (MT) o la síntesi de veu (TTS), ha suposat una millora dràstica en la precisió i qualitat d'aquests sistemes, estenent així la seva implantació a un ventall més ampli a la vida real. En aquest moment, és evident que les tecnologies de reconeixement automàtic de la parla i traducció automàtica poden ser emprades per a produir, de forma efectiva, subtítols multilingües d'alta qualitat de continguts audiovisuals. Això és particularment cert en el context dels vídeos educatius, on les condicions acústiques són normalment favorables per als sistemes d'ASR i el discurs està gramaticalment ben format. No obstant això, al cas de TTS, encara que els sistemes basats en xarxes neuronals han demostrat ser capaços de sintetitzar veu d'un realisme i qualitat sense precedents, encara s'ha de comprovar si aquesta tecnologia és ja prou madura com per millorar l'accessibilitat i la participació en l'aprenentatge en línia. A més, hi ha diverses tasques al camp de la síntesi de veu que encara suposen un repte, com ara la clonació de veu inter-lingüe, la síntesi incremental o l'adaptació zero-shot a nous locutors. Aquesta tesi aborda la millora de les prestacions dels sistemes actuals de síntesi de veu basats en xarxes neuronals, així com l'extensió de la seva aplicació en diversos escenaris, en el context de millorar l'accessibilitat en l'aprenentatge en línia. En aquest sentit, aquest treball presta especial atenció a l'adaptació a nous locutors i a la clonació de veu interlingüe, ja que els textos a sintetitzar es corresponen, en aquest cas, a traduccions d'intervencions originalment en un altre idioma.[EN] In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including computer vision, natural language processing, robotics, and game theory. In particular, the striking success of deep learning in a large variety of natural language processing (NLP) applications, including automatic speech recognition (ASR), machine translation (MT), and text-to-speech (TTS), has resulted in major accuracy improvements, thus widening the applicability of these technologies in real-life settings. At this point, it is clear that ASR and MT technologies can be utilized to produce cost-effective, high-quality multilingual subtitles of video contents of different kinds. This is particularly true in the case of transcription and translation of video lectures and other kinds of educational materials, in which the audio recording conditions are usually favorable for the ASR task, and there is a grammatically well-formed speech. However, although state-of-the-art neural approaches to TTS have shown to drastically improve the naturalness and quality of synthetic speech over conventional concatenative and parametric systems, it is still unclear whether this technology is already mature enough to improve accessibility and engagement in online learning, and particularly in the context of higher education. Furthermore, advanced topics in TTS such as cross-lingual voice cloning, incremental TTS or zero-shot speaker adaptation remain an open challenge in the field. This thesis is about enhancing the performance and widening the applicability of modern neural TTS technologies in real-life settings, both in offline and streaming conditions, in the context of improving accessibility and engagement in online learning. Thus, particular emphasis is placed on speaker adaptation and cross-lingual voice cloning, as the input text corresponds to a translated utterance in this context.Pérez González De Martos, AM. (2022). Deep Neural Networks for Automatic Speech-To-Speech Translation of Open Educational Resources [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/184019TESISPremios Extraordinarios de tesis doctorale