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Artificial intelligence and translation technologies: what is the state of play?

Wednesday, February 3rd, 2021

By Annalisa Sandrelli, Lecturer in English Language and Translation and EMT representative, Master’s Degree in Interpreting and Translation, Università degli Studi Internazionali-UNINT Programme

Università degli Studi Internazionali-UNINT and DGT (Rome Field Office) jointly organised a Translating Europe Workshop (TEW) on Friday 15 January 2021.

The workshop had the aim of giving an overview of the state-of-the-art on neural machine translation and speech recognition technologies. More specifically, the focus of the TEW was on how the latest trends in technology applied to translation and interpreting can support language professionals in their work and at the same time promote linguistic inclusion and accessibility to information, culture and entertainment for the general public in an ever-globalised, multilingual society (e.g. machine translation of public service webpages, automatic subtitling of plenary debates, and so on). In this sense, the workshop was thematically linked to previous events in the TEW series and was aimed at raising awareness about the added value of translation for society.

Originally envisaged as a face-to-face event, the workshop was moved to the Zoom platform in the face of the current COVID-19 crisis. In order to ensure maximum participation, the event was free of charge and no registration was required; in addition, it was also streamed via the DGT YouTube channel Translating for Europe. The working languages were English and Italian and a simultaneous interpreting service was provided as well. Speakers included academics and researchers from universities in Italy, Belgium, Germany, Ireland and the UK, including several EMT members (UNINT, Dublin City University, Ghent and Surrey); in addition, there were representatives of leading Italian companies working in this field, in order to illustrate the current situation and to highlight where R&D on these topics is going.

After the institutional greetings of DGT’s Director-General Rytis Martikonis and of UNINT’s Rector and Dean of the Faculty of Interpreting and Translation, Session 1 was devoted to introducing the two main foci of the workshop, namely neural MT and speech recognition technologies applied to translation and interpreting. The Head of the MT Unit of DGT, Markus Foti, gave a presentation on the eTranslation tool developed at the EU; this was followed by Giuseppe Daniele Falavigna and Marco Turchi, from Fondazione Bruno Kessler, who provided a brief historical overview of Automatic Speech Recognition technology (ASR) and its applications to speech translation, as well as current developments in Computer Assisted Interpreting. Both strands (neural MT and the applications of ASR to translation) were taken up in the presentations by company representatives, namely Luca De Franceschi (Translated) and Gorizio Ciancarelli and Filippo Tessaro (Pervoice). Both companies have developed a range of state-of-the-art proprietary software and are involved in several research projects, some of which were showcased for the first time during the workshop.

An important aspect related to the pervasiveness of MT in professional translation is, of course, post-editing: this was the subject of the thought-provoking presentations by Moritz Schaeffer (University of Mainz-Germesheim) and Federico Gaspari (University for Foreigners “Dante Alighieri”, Reggio Calabria). Error recognition in post-editing is especially crucial when using neural MT, whose output tends to be acceptable on the surface but may, in fact, contain errors of various kinds; in addition, several metrics for evaluating MT quality were discussed.

After a well-deserved lunch-break, the afternoon session opened with Joss Moorkens’  presentation (Dublin City University) on designing and developing an assistive translation tool, i.e. an accessible translation interface. Along similar lines, Claudio Fantinuoli and Bart Defrancq (Mainz-Germesheim and Ghent, respectively) described their project to develop an ASR-based tool designed to assist simultaneous interpreters in the booth.

The issue of how to integrate machines into the translation and interpreting workflow is another hot topic at the moment. Claudio Fantinuoli & Bianca Prandi (Mainz-Germesheim) described an experimental study in which human simultaneous interpreting is compared with the output of a speech translation system, while Elena Davitti and Tomasz Korybski (Surrey) presented two projects, SMART and MATRIC, in which different speech translation workflows are compared. While SMART is focused on fully human interlingual respeaking, MATRIC compares simultaneous interpreting with the output of a workflow made up of a respeaking component (in the same language) and an MT component. Clearly, there is a wide range of possible workflows in which different speech recognition systems (speaker-dependent or speaker-independent) and MT tools can be fruitfully integrated to assist professional interpreters and translators for specific purposes, and the field is still largely unexplored.

The event was extremely interesting and lively and attracted a lot of attention, with 380 Zoom participants in the morning and 260 in the afternoon, and many more watching via streaming on YouTube, which shows that there is a lot of interest in the topics we discussed. If you have missed it, find out all about our speakers and programme on the event web page below and watch the recordings on YouTube, made available in 3 separate sections for your convenience:

Event webpage, with programme, abstracts and speakers’ bio-notes (in English and Italian): https://www.unint.eu/it/calendario-eventi/translating-europe-workshop-2021.html 

AI and translation technologies-Part 1: neural machine translation 

AI and translation technologies-Part 2: post-editing and localisation

AI and translation technologies-Part 3: AI and interpreting

We look forward to your feedback, comments and questions, to keep the ball rolling.

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.