Dr Juan José Arevalillo Doval, CEO/Managing director of Hermes
Quality standardisation in language industry
27 November 2020
Abstract: Quality in the language services industry is a very blurred term, but omnipresent in all activities from the moment a customer requests a translation service to the delivery and final closing of the project. In this process everything is measured and compliance with all requirements is usually a guarantee of success with the customer. In addition, there are numerous quality standards under ISO’s umbrella covering different services and aspects in this industry, which are applied on a daily basis and also form the basis of numerous academic programmes. Knowing this environment is essential for the future professionals so that they can know where they fit into the process and how to behave and act in that process.
Bio: PhD in Translation by University of Malaga, MA in Specialised Translation by the Institute of Modern Languages and Translators by Madrid Complutense University and BA in English Language and Literature by Madrid Complutense University.
In translation industry since 1980, he is the Managing Director at Hermes Traducciones y Servicios Lingüísticos. Previously worked as a freelance translator and as a language specialist and localiser in Digital Equipment Corporation.
A lecturer on Translation at Alfonso X University (Madrid) and International University of Valence (Spain), he is also the professional advisor for future graduates in the former university. He works with other Spanish high-education centres such as Autonomous University of Madrid, Autonomous University of Barcelona and ISTRAD of Seville.
Formerly Vice-president and Treasurer of the European Union of Associations of Translation Companies (EUATC), now he is the EUATC Youth Ambassador to try to cover the gap between university and industry and help new graduates join professional world. He is also the Chairman of the Spanish Association of LSPs (ASPROSET).
Chairman of Spanish Committee for Translation Services at UNE (Spanish Standardisation Association), and one of the creators of EN-15038 and ISO-17100 standards. He is also a member of ISO TC37 Committee for Translation Services.
Prof Mark Shuttleworth, Hong Kong Baptist University
Free translation memory tools: a comparison of some well-known systems.
25 November 2020
The use of translation memory tools is now fairly well embedded within the profession. While many translators are obliged to use one or other well-known system, others who are able to choose for themselves are perhaps confused by the sheer choice of systems that are available. In this talk I will demonstrate Memsource, Wordfast and Matecat and attempt to answer the following two questions: 1) to what extent does a free tool provide you with the functions that are needed to work at a professional level and 2) what are the strengths and weaknesses of each of these three systems?’
Mark Shuttleworth has been involved in translation studies research and teaching since 1993, at the University of Leeds, Imperial College London, University College London and, most recently, Hong Kong Baptist University. His publications include the Dictionary of Translation Studies, as well as articles on metaphor in translation, translation technology, translator training, translation and the web, and Wikipedia translation. More recently he has become interested in the use of digital methodologies in translation studies research. His monograph on scientific metaphor in translation, Studying Scientific Metaphor in Translation, was published in 2017 and he is currently working on a second edition of the Dictionary.
Keynote speaker engagements have included translation studies conferences in Poland, China and Malaysia. He has also addressed industry conferences in the UK, Italy and Brazil on the subject of translation technology and has provided training in the same area in Spain, Italy, Portugal, Finland, Tunisia and Malaysia.
Mark Shuttleworth is a fluent speaker of Russian, German, Polish and French and has some knowledge of a number of other languages including some Chinese. As and when time permits he is active as a translator.
Dr Frédéric Blain, University of Wolverhampton
Shared tasks in NLP
11 November 2020
Shared tasks have an important role of identifying interests for complex problems in a field, as well as to quantify progress made during a given period of time. In this seminar, we will revisit the History and key aspects of shared tasks in the field of Natural Language Processing. I will share with you my experience as co-organiser of the Quality Estimation Shared task at the Conference on Machine Translation (WMT). Finally, we will discuss some ethical considerations that are arising in the field with regard to the organisation and participation to such challenges.
Fred Blain is a Senior Lecturer of Translation Technology at the University of Wolverhampton and a member of the Research Group on Computational Linguistics (RGCL).
Prior to joining RGCL, Fred was a research associate in Machine Translation in Prof. Lucia Specia’s group at the University of Sheffield. There he worked on discriminative training algorithms for Statistical Machine Translation and continuous adaptation from post-editing workflow within the scope of the EU H2020 QT21 project. He then turned to Quality Estimation for Machine Translation, a topic he has been working on since, in close collaboration with Lucia Specia. Together, they successfully secured several research grants (an Amazon Research Award grant, an EAMT grant and more recently Bergamot, an EU H2020 project), leading to many publications and DeepQuest, the first open-source toolkit for quality estimation for neural-based Machine Translation.
Fred holds a PhD in Computer Science from Le Mans Université (France), which he defended in 2013. As a PhD student, he worked on post-editing, continuous adaptation as well as domain and project adaptations for Machine Translation under the supervision of Holger Schwenk (Facebook) and Jean Senellart (Systran). He pursued his PhD work as a postdoctoral researcher at LIUM, the Computer Science Laboratory of Le Mans Université, by joining the EU FP7 MateCAT project. He also has experience in industry having held a research engineer position at Systran during his PhD.
Dr Maria Kunilovskaya, University of Wolverhampton
Linguistic Resources in Practical Translation
This is a two-part hands-on session designed to introduce a range of freely available corpus-based tools and online resources that can be useful to address some of the most typical problems in human translation and in text generation at large. The session will open with the results of the survey offered to the EMTTI 2020 students to explore their interests and technical competence and to fine-tune the content of the Special Seminar to their needs. I will highlight the cognitive affinity between translation process and corpus use, and the typical problems in practical translation that can be solved with corpora. The main part of the session will cover some basic corpus linguistic terms and demonstrate several online query interfaces. Most of this part of the session is designed to allow shadowing to facilitate “learning-by-doing” approach in education.
The second part of this session provides details on more sophisticated types of queries, but mostly it is a follow-up on the few practical assignments offered for independent study. The session aims to provide working query skills to entice further research into using corpora and to whet your appetite for more.
Suggested background reading:
Thomas, James: Discovering English with Sketch Engine: A Corpus-Based Approach to Language Exploration. 2nd ed. Brno: Versatile, 2016. 228 pp. (Reviewed in Kunilovskaya, Maria and Kovyazina, Marina (2017). Sketch Engine: a toolbox for linguistic discovery. In Journal of Linguistics, Slovak Academy of Sciences, Vol 68, No 3, 503-507. DOI: 10.2478/jazcas-2018-0005. https://www.sketchengine.eu/wp-content/uploads/Sketch_Engine_Toolbox_2017.pdf)
Maria Kunilovskaya has been engaged in translator education for more than 10 years in her role as an Associate Professor in Contrastive Linguistics and Translation Studies at the University of Tyumen, Russia. Lecturing in Translation Studies, Corpus Linguistics and Text Linguistics, she has also been involved with teaching practical translation classes. She is a strong believer in promoting practical corpus skills that can be immediately applied in everyday activities of a language professional. Her research interests include construction and exploitation of parallel corpora, corpus-based research into translation competence and translationese, most recently with a strong pull towards the computational research methods, especially in the area of human translation quality estimation.
Dr Elizabeth Deysel
An Overview of Technology for Interpreters – the what and the why?
23 October 2020
Elizabeth Deysel has been working in the field of interpreting for the past ten years. She is currently employed as an interpreter in the National Parliament of South Africa where she has been interpreting for the past six years. She previously lectured and trained interpreters at the University of the Free State before moving to Stellenbosch where she worked as an educational interpreter. She completed her Masters in Interpreting which focused on computer assisted interpreter training (CAIT) and how it may be used to improve self assessment skills of the professional interpreters. She is currently pursuing her PhD in Interpreting at Stellenbosch University with a specific focus on Interpreting Technology and the implementation thereof in the curriculum for training interpreters. As you may have guessed, she is a lover of “gadgets” and all things tech related especially technology for interpreters.
The webinar starts with a brief introduction on the history of technology and interpreting. It then provides a broad overview on technology and interpreting and what tools are currently available and used most frequently in practice. The two types of technologies to be discussed are: 1) process orientated technologies which provides support to the interpreter and 2) setting orientated technologies which shape and change the way interpreting is delivered.
Dr Burcu Can, University of Wolverhampton
How to Represent Words?
4 December 2020
Agglutinating languages are built upon words that are made up of a sequence of morphemes. Although the morphemic structure of a language enables a productive word generation that handles both syntax and semantics during the generation of new words, in other respects this production causes sparsity in the language, thereby brings one of the most challenging problems in natural language processing.
The sparsity problem is still there with the rise of representation learning with which we could represent each word in a low dimensional space using their distributional features in a large corpus. However, if the word does not exist or it is not frequent enough, how should we represent this word in the same space? Most of the recent work handles this problem by processing each word as a set of characters where the representation is obtained through a word’s characters. Here I will describe our recent model, morph2vec, by questioning whether a word should be represented by its characters or its morphemes. How to represent words in agglutinating languages?