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A microdegree program on translation technology and machine translation

Monday, June 27th, 2022

By Reelika Saar, Junior Lecturer, University of Tartu, Master’s in Translation Studies

Quick technological development and the changes to the job market that come with it also have a very strong influence on the educational landscape. A notable development is the increase in the demand for flexible options for continuing education and retraining that allow students to adapt to the changing situation without having to dedicate several years to their studies. In addition to the traditional one-off continuing education courses, microdegree programs (or micro-credentials) are a clear example of this flexible learning, and several Estonian universities have recently started offering them (University of Tartu 2022, TalTech n.d, Tallinn University n.d, Estonian University of Life Sciences n.d, Estonian Academy of Security Sciences n.d). Microdegree programs are comprehensive continuing education programs, meant to allow students to upskill themselves, make themselves more competitive in the job market and/or support a change in career; they also serve to give the student a better idea of whether the formal education (degree) options on offer are a good choice for them (University of Tartu 2022). Such shorter and more flexible study programs are quickly becoming common throughout all Europe and worldwide (European Commission n.d).

Source: unsplash.com

In the 2021-2022 academic year, the Department of Translation Studies of the University of Tartu offered for the first time the microdegree program “CAT tools, machine translation and web-based tools on the basis of EU texts” (12 ECTS), which brings together three courses. Two of the courses deal with technological facets of the translation profession which grow in importance every year: CAT tools, translation memories and machine translation. The third focuses on the particularities of translating texts connected to the European Union (EU), including the use of sources (such as EUR-Lex and the IATE terminology database) and tools (like the machine translation system eTranslation) which are especially important when working with EU documents. These microdegree courses very closely match the equivalent courses in the master’s program in Translation Studies, with only minor changes made to adapt them to the continuing education context, since all the University of Tartu’s microdegree programs are built with the intention to allow graduating students to continue their studies through a full degree program if they so desire (University of Tartu 2022).

The first edition of the microdegree program offered by the department of Translation Studies lasted two semesters, and 23 students registered to participate. The number of students was limited to allow the lecturer to provide some degree of individual feedback to every one of them. Even though the intended main target group of the microdegree program was professional translators and revisers, a survey carried out at the start of the program revealed that around half of the students had not actually done any translating nor revising on a professional level, which shows that microdegree programs can be of great interest to people who are specifically looking for a way to retrain and change their careers. To ensure the highest level of flexibility, especially considering the effects of the COVID-19 pandemic, the microdegree program was taught fully online, with live webinars every other week on the BigBlueButton teaching platform. In between webinars, the students received exercises and teaching materials for individual learning (including screen recordings) through the Moodle platform. In addition to said screen recordings, recordings of all live webinars were also shared with students in Moodle for watching later. Even though recordings were made available, more than half of the students opted to attend the webinars live during the autumn semester. The program participants were also offered the option to join the university students during their lessons (for example to use the university’s computer classroom), but at least this year they preferred to do all their learning online. Any questions the students had between webinars could be asked from the lecturer through a web form or via email, and the students also had the option to communicate with each other through forums on the Moodle platform. The questions sent to the lecturer were answered either directly via email or, in some cases, as part of the next webinar, serving as a basis for a wider group discussion on the topic.

The production of screen recordings allowed students to go through the study materials at their preferred speed, and to review them later if desired. The recordings were made available through the Panopto platform, which also provides statistics about which videos students actually watched and for how long. These statistics provided the lecturer with clues about the topics which the students might have found especially difficult and to which more time needed to be dedicated. In addition to the attainment of specific technical skills, the courses that were part of the microdegree also put importance on learning from real-life situations and the analysis of possible problems and risks connected to them, including in connection with the importance of ethics in translation training (about which Joss Moorkens (2022) recently wrote in the EMT blog).

At the time of writing the current post (June 2022) the microdegree program has reached its last week, during which the participants will complete the last exercises and get the chance to give feedback about the whole program. So far, the individual feedback received has been positive and has shown that a microdegree program can be a valuable way of improving existing skills and attaining new ones not only for professional translators and revisers, but also, for example, for people interested in a career change into translation. Hopefully once all feedback has been received and analyzed it will be possible to better evaluate the program (whether its duration is adequate, the pros and cons of it being fully web-based, how well it matched the expectations of the target groups, etc.) in order to improve it further. It is clear that there is an interest in this form of continuing education, since several would-be participants have themselves contacted the university and inquired about the registration options for the next edition of the program after seeing information about the current one online. We have also seen that continuous education can give participants a push to continue their studies by working towards a master’s degree in the Department of Translation Studies.

References:

Estonian Academy of Security Sciences. (n.d).Mikrokraad – amps kõrgharidusest! https://www.sisekaitse.ee/en/node/5455?language_content_entity=en (15.06.2022)

Estonian University of Life Sciences. (n.d). Mikrokraadiprogrammid. https://mikrokraadid.emu.ee/mikrokraadiprogrammid/ (15.06.2022)

European Commission. (n.d). A European approach to micro-credentials. https://education.ec.europa.eu/education-levels/higher-education/micro-credentials (15.06.2022)

Moorkens, J. (2022). Incorporating ethics in translation programmes. EMT blog. https://blogs.ec.europa.eu/emt/incorporating-ethics-in-translation-programmes/

Tallinn University. (n.d).  Mikrokraadid. https://www.tlu.ee/mikrokraad (15.06.2022)

TalTech. (n.d).  Avatud õpe, mikrokraadid. https://taltech.ee/avatud-ope/mikrokraadid (15.06.2022)

University of Tartu. (2022).  Mikrokraadiprogrammid. https://ut.ee/et/mikrokraadid

Incorporating ethics in translation programmes

Tuesday, May 24th, 2022

By Dr Joss Moorkens, Dublin City University, School of Applied Language & Intercultural Studies.

There is a growing consensus on the importance of ethical training as part of university programmes. More broadly, there’s a growing interest in transversal skills. These are interdisciplinary skills that are applicable in many situations and fields and could be useful for all graduates. As part of a recent development exercise at Dublin City University, we developed a set of learning outcomes for such skills, including ethical decision-making. In the European Masters in Translation Network we are currently revisiting our Translation Competence Framework for the next round of programme applications and the inclusion of ethics is an important consideration.

Source: www.manypixels.co

In the past, ethics have mostly been applied to translation in the form of rules and guidelines for individual translators or for translation companies. In ethics, this is known as the deontological approach to ethics, and can be useful for encouraging ‘good’ decisions and to signal trustworthy and professional behaviour within the industry. However, guidelines cannot possibly cover every situation or eventuality, so we have other ethical tools and theories to help us to make better ethical decisions. The consequentialist approach, for example, leads us to consider the best result for most people, stakeholder theory is useful to think of different groups of people affected by a decision, care ethics helps us to focus on the most vulnerable, and virtue ethics provides a set of sample virtues that might help us to flourish as humans, either alone or as part of an organisation.

As the technological tools that we use every day have matured, there has been a growing awareness of ethical issues in technology. Winner (1983) wrote about how technologies engender their own worlds, and Kranzberg (1986) opined that technologies are not good or bad, but nor are they neutral. Contemporary writing on technology ethics looks at social and political contexts and interactions with power interests to identify ethical issues, often regarding machine learning or applications of artificial intelligence. Machine learning systems search for patterns in data, making predictions based on their findings. They operate by inference rather than following a direct command, their output can be opaque, biased, and unpredictable. Researchers have found issues and biases in the output from machine learning systems such as those applied to facial recognition, text creation, and machine translation.

Current machine translation systems are usually based on huge corpora of translation data, bringing to the fore issues of data ownership, data security, and data literacy. Venuti wrote about translation copyright as far back as 1998, and the Bird and Bird report (Troussel and Debussche 2014) provided great insights in the area, but ownership and control of translation data have arguably never been more important than in the neural machine translation era. The European Union has set limits on the use and reuse of personal data and made publicly funded EU translation data available globally, but the production and reuse of privately funded translation tends to be limited. Projects such as the forthcoming Common European Language Data Space will help to democratise access to data, but without the necessary computing power and technological skills, not everyone can maximise the benefits of such language data. There are lots of other ethical issues related to human and machine translation, such as risk and liability in the case of mistranslation or a data breach, computing cost and related carbon imprints, bias and misrepresentation in output, and fairness of working conditions in a part-automated translation workflow.

Translation may be considered a canary in the coalmine for the application of artificial intelligence in an industry. Repeated surveys (e.g., Pielmeier and O’Mara 2020) suggest that over 70% of professional translators work on a freelance basis, a rate higher than in many other industries, making it difficult to effectively act collectively, even within professional organisations. Retrospective analyses suggest that machine translation post-editing has represented roughly 4% of annual translation turnover in recent years (see CSA Research 2019) in a consistently growing industry, but we can probably assume that it’s available as an input for a larger proportion of translation work. The expectation is that machine translation – a key application of artificial intelligence — will make further inroads in the coming years (ELIS Research 2022). We also see new applications of artificial intelligence to translation in areas such as quality evaluation, freelance translator contracting, and predictive pricing. It is thus important that translation graduates, as future decision makers, are prepared to consider the ethical aspects and impacts of their decisions based on readings on theoretical and applied ethics alongside their translation and technical competences. Ethical decision-making is not only good for the sustainability of the industry (and our programmes), but it is also a valuable skill that can be applied in other industries and situations as graduates move through their careers in an increasingly dynamic work environment.

Some useful resources for translation and ethics include:

Kenny, Dorothy (Ed.) 2022 (forthcoming) Machine translation for everyone: empowering users in the age of artificial intelligence. Berlin: Language Science Press.

Koskinen, Kaisa and Nike K. Pokorn (Eds.) 2021. The Routledge Handbook of Translation and Ethics. Abingdon: Routledge.

Parra Escartín, Carla and Helena Moniz (Eds.) 2022 (forthcoming). Ethics and Legal Issues in Machine Translation. Berlin: Springer.

Pym, Anthony. 2012. On translator ethics: Principles for mediation between cultures. Amsterdam: John Benjamins.

References

CSA Research. 2019. The Largest Language Service Providers: 2019. Boston: CSA Research.

ELIS Research. 2022. European Language Industry Survey. Brussels: ELIS Research.

Kranzberg, Melvin. 1986. “Technology and History: “Kranzberg’s Laws.” Technology and Culture 27:544–560.

Pielmeier, Hélène, Paul O’Mara. 2020. The State of the Linguist Supply Chain. Boston: CSA Research. https://insights.csa-research.com/reportaction/305013106/Toc

Troussel, Jean-Christophe and Julien Debussche. 2014. Translation and Intellectual Property Rights (Report by Bird & Bird for the European Commission DG Translation). Luxembourg: Publications Office of the European Union.

Venuti, Lawrence. 1998. The Scandals of Translation. Abingdon: Routledge.

Winner, Langdon. 1983. “Technologies as Forms of Life”. In: Cohen R. S., Wartofsky M. W. (Eds.) Epistemology, Methodology and the Social Sciences. Reidel, Dordrecht, pp. 249–263.

Machine Translation or the Nutella® Ordeal

Wednesday, December 16th, 2020

By Jean-Yves Bassole, dr.Phil. dr.Litt., Head of the Institute of Translators, Interpreters and International Relations (ITIRI), Faculty of Modern Languages, University of Strasbourg, France.

Translated from French by Duncan Miller, MSc by Research in Science and Technology Studies, MA in Professional Translation, sworn Translator/Interpreter at the Court of Appeal of Colmar, lecturer at the Institute of Translators, Interpreters and International Relations (ITIRI), Faculty of Modern Languages, University of Strasbourg, France.

Translation lecturers are increasingly confronted with a threatening reality, which is likely to be detrimental to their lessons: machine translation. Admittedly, this subject is taught as such and translation courses include postediting lessons. However, it is often too big a temptation. Some students cannot avoid using a variety of machine translation tools, kindly made available by the companies that produce them. Who would easily turn down a jar of Nutella? Let’s be honest, everyone can understand this temptation. Who has never given into it?

Actually, the succumbence to this temptation is not what bothers us the most. No one can possibly criticise students for using all the available tools. After all, is that not what we recommend them to do on the day they become our colleagues, as translators? We are not concerned about them using these tools as such, we are concerned they will use them too early, without initially attending the appropriate lessons, which are designed to raise their awareness of the advantages and drawbacks of the given tools.

Therefore, from a lecturer’s perspective, the following question should be addressed. If students do not have the patience to wait for the right moment to use the aforementioned tools, wouldn’t it be wiser to redesign our courses by including an introduction to these tools at an earlier stage? The answers vary according to different countries, cultures and universities. The answer to this question is also linked to the inherent structure of translation studies. Some university systems consider that translation can already be studied in first year, while others consider that sound linguistic and cultural knowledge is required before focusing on translation itself.

This is the case for the Institute of Translators, Interpreters and International Relations (ITIRI), Faculty of Modern Languages, University of Strasbourg, where translation studies start in the first year of the Master’s programme. Access is granted to candidates with a three-year university experience (in languages, literature, law or any other subject), who pass the admission tests, which are conducted to ensure their linguistic and cultural background is sufficient.

Noticeably, our conception is defined by a minimum required to reach the next level. Under these circumstances, it is hardly surprising that we only provide postediting lessons in the second year of the Master’s degree in Professional Translation, Literary Translation and Audiovisual Translation and Accessibility. For us, it seems obvious that machine translation tools can only really be useful when students are sufficiently trained in translation.

Considering the stance of the lecturers and the aforementioned temptation of the students, the only viable solution consists in informing the first-year Master’s degree students about the inherent dangers of machine translation tools. It is with this in mind that I will deliver a speech, at the next congress organised by ITIRI, entitled ROBOTRAD, which is scheduled for autumn 2021. I will endeavour to present what I try to demonstrate to our students, that in general no one can become a virtuoso without studying music theory beforehand.

Some of our translation lecturers sometimes give their students a text to translate along with several “translations” generated by machine translation tools. This highly pedagogical approach, that I would in fact compare to some sort of mine-clearing, is generally carried out with texts associated with so-called “pragmatic translation”. In contrast, I decided to conduct the experiment on texts from twentieth century authors, but with a preference for extracts which are more based on spoken language.

This is how I managed to select an array of vocabulary, syntax and morphology difficulties, along with a few flashes of wit. These sentences or groups of sentences were submitted to five machine translation engines, to be translated into English. The chosen methodology consisted in submitting a sentence to the five engines, on the same day and virtually at the same time. This same procedure was repeated twice, after a minimum period of twenty-four hours, in order to confirm or disconfirm the stability of the answers. The same procedure was carried out from two other workstations.

Without going into the details of the findings, three significant trends immediately arose:

– In numerous cases, the generated translation presents no sense of stability: the same sentence may be translated differently by the same translation engine at a twenty-four or forty-eight hour interval;
– The generated translations from one workstation to another do not present a sense of stability either;
– The expressions related to spoken language or humor are rarely identified.

As a case in point, here are a few translations obtained for the title of this post that I would have modestly translated as “Machine Translation or the Nutella Ordeal”: 

The machine translation or the torment of Nutella.

Machine translation or the torment of Nutella.

Machine translation or Nutella supplementation.

Machine translation or Nutella torture.

With regard to the proposed translations, we can notice there are as many perceptible improvements as there are astonishing deteriorations.

The students very quickly come to the conclusion that they cannot trust such translations. Owing to the multiplicity of the solutions, they become aware of the inconsistencies, the variability from one workstation to another, and the necessity to err on the side of caution. They realise that these tools, which are freely made available on the internet, are not really going to help them but are more likely to turn into time-consuming traps.

Once they are aware of this, the students often manage to identify the repeated faulty tricks. Sometimes, they even manage to provide an explanation for certain types of deficiencies. Undoubtedly, from then on, they are ready to resume their training without taking the risk of being lured by the machine translation mermaids. Once passed this first level, they will also be ready to take on postediting lessons, in a confident manner.

Google Translate

Automatic translation or the torment of Nutella®

Translation teachers are more and more often confronted with a threatening reality which is likely to affect their lessons: machine translation tools. Of course, this subject is taught as such and translation courses generally provide for post-editing courses. Yet the temptation is often too great: some students cannot help but use various machine translation tools made available to them free of charge by the companies that have developed. Who would give up a jar of Nutella without flinching? Let’s put it bluntly, we can all understand this temptation – who has never succumbed to it?

What really bothers us the most is not that the temptation materializes – no one can criticize their students for using all the tools at their disposal. Isn’t that ultimately what we will be asking them to do the day they become our colleagues in the profession of translator? No, what bothers us is not that they do it, but that they do it too early, without having previously taken the appropriate courses, which are likely to make them aware of the strengths and weaknesses of the instruments offered.

A question then arises, on the teachers’ side: if students do not have the patience to wait for the right moment to use the aforementioned tools, would it not be wise to rethink our courses by integrating earlier contact with these? instruments? Answers vary by country, culture and institution. The answer to this question is also linked to the very structure of translation studies: some university systems consider that one can start studying translation from the first year of the license, others consider that it is necessary first to have acquired solid linguistic and cultural foundations before starting the practice of translation.

This is the case of the Institute of Translators, Interpreters and International Relations (ITIRI), Faculty of Languages, University of Strasbourg: translation studies begin in the first year of the master, the entry ticket being made up of, ” on the one hand, three years of university studies (in languages, humanities, law or any other field) and, on the other, success in admission exams aimed at ensuring linguistic level and background cultural background of the candidate.

As we can see, our conception is that of a minimum required to move to the next level. Under these conditions, we should not be surprised to see us maintain post-editing courses in the second year of the master’s degree in professional translation, literary translation or audio-visual translation and accessibility. It seems obvious to us that machine translation tools can only be of real use when the student is already sufficiently trained in translation.

Faced with this choice in principle of the trainers and the student temptation mentioned above, the only viable solution consists in informing the first year master’s students of the dangers inherent in automatic translation tools. It is in this spirit that I will present a paper at the next congress organized by ITIRI, entitled ROBOTRAD, which is scheduled for the fall of 2021. I will endeavor to expose what I am trying to demonstrate to our students, to know that as a general rule no one becomes a virtuoso without having studied music theory.

Some of my translation colleagues sometimes give their students a text to translate along with several “translations” provided by machine translation tools. This highly educational operation, which I would consider altogether to a kind of demining, is generally carried out on texts relating to what has come to be called pragmatic translation ’. For my part, I wanted to experiment with texts taken from 20th century authors but with a preference for passages that are more related to the spoken language.

This is how I was able to select a palette of difficulties, vocabulary, syntax or morphology, without forgetting one or two wit. These sentences or groups of sentences were submitted to five machine translation engines for translation into English. The methodology adopted consisted in submitting a sentence to the five engines on the same day, practically at the same time. This same procedure was repeated twice, after a minimum of one day, the objective being to confirm or not the stability of the responses. The same procedure was implemented from two other workstations.

Without going into the details of the findings here, three main lines immediately emerged:

in many cases, the proposed translation does not present any stability character: the same sentence can be translated in a different way by the same translation engine 24 or 48 hours apart;the translations offered from one workstation to another are not stable either;expressions relating to spoken language or humor are often not identified.

– in many cases, the proposed translation does not present any stability character: the same sentence can be translated in a different way by the same translation engine 24 or 48 hours apart;
– the translations offered from one workstation to another are not stable either;
– expressions relating to spoken language or humor are often not identified.

By way of illustration, here are the translations obtained for the title of this post, which I humbly translated « Machine Translation or the Nutella Ordeal »:

The machine translation or the torment of Nutella.

Machine translation or the torment of Nutella.

Machine translation or utella supplementation.

Machine translation or Nutella torture. 

With regard to the proposed translations, there are as many appreciable improvements as there are astonishing deteriorations.

Very quickly, the students come to the conclusion that they cannot trust these translations. They discover, through the multiplicity of solutions, the lack of stability of responses and their variability from one workstation to another, the need to be wary, to doubt and to consider that these tools, made available free of charge on Internet, are not likely to help them but can rather constitute a trap which will make them waste more time than it will save them.

This once understood, the students often manage to identify wrong turns which are repeated; sometimes they even manage to offer an explanation for certain types of deficiencies. There is no doubt then that they are ready to continue their training without risking being seduced by the sirens of machine translation; they will also be ready, once this first cycle is completed, to approach post-publishing courses with confidence.

DeepL (free version)

Machine translation or the torture of Nutella®

Translation teachers are increasingly confronted with a threatening reality, which is likely to affect their lessons: machine translation tools. Admittedly, this subject is taught as such and translation curricula usually include post-editing courses. However, the temptation is often too great: some students cannot help but resort to various machine translation tools made available to them free of charge by the companies that developed them. Who would give up a jar of Nutella without flinching? To put it bluntly, we can all understand this temptation – who has never succumbed to it? 

What really bothers us most is not that the temptation actually materialises – no one can criticise their students for using all the instruments at their disposal. Isn’t that what we advise them to do when they become our colleagues in the translation profession? No, what bothers us is not that they do it, but that they do it too early, without having first attended the appropriate courses, which are likely to make them aware of the strengths and weaknesses of the instruments offered.

A question then arises on the teachers’ side: if students do not have the patience to wait for the right moment to use the above-mentioned tools, would it not be wise to rethink our curricula by integrating earlier contact with these instruments? Answers vary from country to country, culture to culture and institution to institution. The answer to this question is also linked to the very structuring of translation studies: some university systems believe that one can start studying translation as early as the first year of the bachelor’s degree, while others consider that one must first have acquired a solid linguistic and cultural basis before starting to study translation.

This is the case at the Institute of Translators, Interpreters and International Relations (ITIRI), Faculty of Languages, University of Strasbourg: translation studies begin in the first year of the master’s degree, the entry ticket consisting, on the one hand, of three years of university studies (in languages, literature, law or any other field) and, on the other hand, the successful completion of entrance exams aimed at ensuring the candidate’s linguistic level and cultural background.

As you can see, our conception is that of a minimum requirement to move to the next level. Under these conditions, it should come as no surprise that we maintain the post-edition courses in the second year of the Master’s degree in Professional Translation, Literary Translation or Audiovisual Translation and accessibility. It seems obvious to us that machine translation tools can only be of real use when the student is already sufficiently trained in translation.

Faced with this choice of principle by the instructors and the student temptation mentioned above, the only viable solution is to inform first-year master’s students of the dangers inherent in machine translation tools. It is in this spirit that I will be presenting a paper at the next congress organised by ITIRI, entitled ROBOTRAD, which is scheduled for autumn 2021. In it, I will attempt to explain what I am trying to demonstrate to our students, namely that as a general rule, no one becomes a virtuoso without having studied solfeggio.

Some of my colleagues who teach translation sometimes give their students a text to be translated accompanied by several ‘translations’ offered by machine translation tools. This highly educational operation, which I would describe as a kind of mine clearance, is generally carried out on texts that fall within the scope of what is known as ‘pragmatic translation’. For my part, I wanted to experiment with texts drawn from 20th century authors, but with a preference for passages that are more relevant to the spoken language.

This enabled me to select a range of difficulties, vocabulary, syntax or morphology, not forgetting one or two witty features. These sentences or groups of sentences were submitted to five machine translation engines for translation into English. The methodology used consisted of submitting one sentence to the five engines on the same day, at practically the same time. This same procedure was repeated twice, after a minimum delay of one day, with the aim of confirming or not the stability of the responses. The same procedure was carried out from two other workstations.

Without going into the details of the findings here, three broad outlines immediately emerged:

– in many cases, the proposed translation is not stable: the same sentence can be translated differently by the same translation engine 24 or 48 hours apart;
– the translations offered from one workstation to another are not stable either;
– expressions in the spoken language are not often identified.

By way of illustration, here are the translations obtained for the title of this post, which I would have humbly translated « Machine Translation or the Nutella Ordeal » :

The machine translation or the torment of Nutella.

Machine translation or the torment of Nutella.

Machine translation or utella supplementation.

Machine translation or Nutella torture.

As far as the proposed translations are concerned, there have been as many significant improvements as astonishing deteriorations

Very quickly, students come to the conclusion that they cannot rely on these translations. They discover, through the multiplicity of solutions, the lack of stability of the answers and their variability from one workstation to another, the need to be wary, to have doubts and to consider that these tools, made available to them free of charge on the Internet, are not likely to help them but can rather constitute a trap that will make them lose more time than they gain.

Once this is understood, students often manage to identify repeated wrong turns; sometimes they even manage to offer an explanation for certain types of disabilities. There is no doubt that they are ready to continue their training without the risk of being seduced by the sirens of machine translation; they will also be ready, once this first cycle is completed, to tackle the post-editing courses calmly.

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