Technologies for Translation and Interpreting: Challenges and Latest Developments

19 November 2021

Speaker: Rocío Caro, University of Wolverhampton

Title: Integration of TM and MT


Translation Memories (TM) and Machine Translation (MT) have been used by translators for a long time, but research has mainly studied them separately until very recently. Nowadays, however, not only academic research is focused on the integration of TM and MT, but many CAT tools include the possibility of working with an MT engine as well. Some companies claim that the integration of the two technologies is beneficial for translators as it may increase their productivity, but there are not comprehensive studies on the topic and very little is known about the efforts, productivity and opinion of translators on using translation tools that integrate TM and MT, and the quality of the final texts.

In the first part of the talk, I will present the different ways TM and MT can be integrated, which are divided into two main categories: internal or external integration. In the second part, I will present the project we are currently carrying out to study the post-editing efforts (technical, temporal, and cognitive) of translators working in an external integrated environment (i.e., both TM and MT segments are presented to the translator), the preliminary findings, what we found about the opinion of translators, and the next steps of the project.


Rocío Caro is currently doing her PhD in Translation Technology at the Research Group of Computational Linguistics, University of Wolverhampton. She has an MA in Translation for the Publishing World and a BA in Translation and Interpreting from the University of Malaga, Spain.

Technologies for Translation and Interpreting: Challenges and Latest Developments

19 November 2021

Speaker: Dr Antonio Toral, University of Groningen

Title: Machine-Aided Literary Translation: State of Affairs in the Early 2020s


To what extent can machine translation be used to translate literary texts? Could such machine translations be of any use to professional literary translators? Could readers benefit in any way from the resulting machine-aided translations?

Through these and other related questions, I aim to present the current state of affairs concerning the application of machine translation to literary texts, focusing on fiction. Taking into account the shortcomings encountered to date, I will then outline potential lines of research that may occupy us in the first half of the 2020s.


Antonio Toral is an Senior Lecturer in Language Technology at the University of Groningen. He holds a PhD in Computational Linguistics from the University of Alicante and has carried out research in the area of Machine Translation (MT) since 2010. His research interests include the application of MT to literary texts, MT for under-resourced languages and the analysis of translations produced by machines and humans.

Technologies for Translation and Interpreting: Challenges and Latest Developments

12 November 2021

Speaker: Dr Celia Rico, Machine Translation Specialist

Title: Translation and machines: artefacts, instruments and the evolving role of the translator


The advent of neural machine translation has undoubtedly affected the translation industry, speeding up the digitalization process, taking translator productivity to new heights, and lowering production prices. One of the immediate consequences is the gradual depletion of the traditional role of translators, who see their work reduced to the revision of isolated segments produced by a machine. The risk of translation becoming a marginal activity is high (Pym 2014, 37) if the task is simplified in the mechanical substitution of words and phrases detached from the communicative context in which they originated. We can even think of the subrogation of the essential work of translators, who are forced to leave their main job in the hands of the computer.

This trend, which, on the other hand, is not alien to other production processes or services, can be explored in the light of a tension between “artefacts” versus “instruments” (Alonso and Calvo 2015): an artefact is an isolated object that performs a series of functions without having any relationship with its user, while the instrument is associated to the user as an essential part of a process. From this perspective, we can analyse both the technological object itself and the different ways in which users (or society, by extension) interact with it.

In this talk, I will use this framework to analyse the changes that the latest developments in machine translation have brought to the job profile and workflows of professional translators. My contention is that linear processes of translation that conceive machine translation as an artifact are obsolete, and that only by considering this technology as an instrument can translators remain in control of the process.


Celia Rico holds a Ph.D. in Linguistics, an MSc in Machine Translation and an MBA. With an extensive background in Translation Technologies research, Dr. Rico’s publications have concentrated on areas such as translation memory evaluation, machine translation, post-editing, and the impact of new technologies on the translation profession. Her major contributions to this field are to be found in different international publications. She is member of the Expert Committee “Post-editing of Machine Translation Output” at ISO TC37.

Search Solutions Tutorial on Natural Language Processing.

Dr Michael Oakes

Search Solutions is an annual event run by the Information Retrieval Specialist Group, the section of the British Computer Society which has a special interest in search engines. This year it took place on Wednesday 24th November, and was held online for invited speakers from industry to talk about their work in information retrieval. The British Computer Society has new offices at 25 Copthall Avenue in London, near the Bank of England. On the day before, a series of tuorials designed to introduce people to related topics were held, such as one given by Ingo Frommholz from our own computing department on search engine evaluation.

The tutorial on Natural Language Processing was given by myself. Unlike the others, it was an all-day event, and held face-to-face. After having had experience of online teaching during the pandemic, I know that I prefer the closer interaction with the students which comes with face-to-face teaching.

The contents of the tutorial were almost the same as the first three weeks of lectures that I give on the MA Computational Linguistics module in RIILP. I used the structure of the textbook by Jurafsky and Martin as a skeleton, but brought in other things such as the practical exercises  from the Edinburgh Textbooks in Empirical Linguistics on stemming and automatic part of speech tagging. Stemming covers techniques for regarding different grammatical forms of a word as being related to each other, and part-of-speech tagging is assigning a part-of-speech category (such as noun or verb) to each word in the input sentence. I used the first edition of Jurafsky and Martin to open the discussion with a short dialogue between Dave the astronaut and HAL the computer from the film “2001 – A Space Odyssey”. What natural language techniques would HAL need to know to carry out this conversation?

At the event, I was pleased to see some old friends in the audience, including Ingo in the morning, before his own workshop began.  

More details are available at:

VC Award Logo

Winners of the Vice-Chancellor’s Awards for Staff Excellence

Earlier this week the Vice-Chancellor’s Awards for Staff Excellence took place. Our Admin Team – April, Suman, Kate, Amanda and Emma – were nominated and won their category of ‘Excellence in partnerships’. If you were unable to join the event, you can watch it back on YouTube. The staff awards brochure can now also be viewed online, which includes an overview of all the shortlisted nominees. 

Excellence in partnerships 

“An individual or a team that has demonstrated outstanding commitment and professionalism through partnership working, to a high-quality service to our students, staff or stakeholders”. 

Winners: RIILP Administrative Team: April Harper, Amanda Bloore, Suman Hira, Kate Wilson, Emma Franklin for supporting the institutional research trajectory by providing infrastructure, systems and processes as well as a positive attitude.

Congratulations Ladies!

Technologies for Translation and Interpreting: Challenges and Latest Developments

Dr Maria Kunilovskaya, University of Wolverhampton

05 November 2021

Title: Human Translation Quality Estimation and Translationese


In the first part of the talk I will present a fairly novel NLP task of human translation quality estimation (HTQE) and discuss problems associated with benchmarking human translation quality. How far do human assessors agree on (human) translation quality? What types of labels/scores can be used to reflect quality? What are the existing approaching to predict these labels? If a professional jury in a translation contest manages to achieve agreement on the top-ranking and, especially on bottom-ranking, translations (with possible fine-grained disagreements about the exact ranks) what does it take to teach a machine to distinguish between good and bad translations? Such a model can be applied in educational and certification contexts for filtering out translations that are definitely below the expected standard to reduce the workload for human assessors. The second part of the talk will explore the concept of translationese, and its potential for learning human translation quality. Do you expect good translations to read smoothly and naturally as if originally-written in the target language? Can we use the distance between translations and the expected target language norm to measure translation quality? I will largely draw on the findings reported in our latest publications: 

  • Kunilovskaya, M. and G. Corpas Pastor (2021). Translationese and register variation in English-to-Russian professional translation. In L. Lim, D. Li, and V. Wang (Eds.), New Perspectives on Corpus Translation Studies. Springer. 
  • Kunilovskaya, M., Lapshinova-Koltunski, E., & Mitkov, R. (2021). Translationese in Russian Literary Texts. Proceedings of the 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. EMNLP.


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.