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The use of eTranslation in the tourism industry

Monday, August 16th, 2021

By Pr. Titika Dimitroulia, Professor of Translation Studies, Director of the Translation Sector of the School of French at Aristotle University, Scientific coordinator of the Apollonis project AUTH (Clarin-el), tutor on the University’s EMT programme and Leonidas Kourmadas, Translator in the Greek language department of DG Translation at the European Commission, currently DG Translation Field Officer at the Commission representation in Athens.

Tourism is one of the world economy’s “heavyweight” industries and, according to the World Tourism Organisation 2020 report, “Europe accounts for half of the world’s international arrivals”, with Southern Mediterranean destinations leading the sectors’ European growth (+5 tourist arrivals, +7 tourism receipts, p. 10).

Figure1. UNWTO Tourism Highlights, 2020 Edition, p.7.

As might have been expected, the pandemic, played down this growth, but this does not diminish tourism’s long-term importance in the global, and in particular in the European economy. Nevertheless, the pandemic stressed even more the need for sustainable tourism development, which, according to UNEP and UNWTO (2005, 11-12), presupposes optimal use of environmental resources, enhancing of inter-cultural understanding and tolerance, as well as viable, long-term economic operations with fairly distributed benefits to all stakeholders, while ensuring a high level of tourist satisfaction. Consequently, information and communication constitutes the core of sustainable tourism development at all levels, shaping not only a destination’s image and assessment, but also the attitudes and behaviour of those who visit it.

Besides the traditional forms of marketing and communication, today, websites and social media are a prime source of information on tourism experiences and they play an important role in tourists’ decision-making process (Liu, Mehraliyev, Liu & Schuckert 2020). They are equally important in the evaluation of services and help shape the image of individual businesses and destinations, with language playing an important role in tourists’ choices: the dominance of English as a “lingua franca” may be undisputed in tourism also, however, many surveys show that tourists prefer to communicate in their mother tongue and tend to evaluate positively the provision of services in their language. As pointed out by de Carlos, Alén, Pérez-González and Figueroa (2019, 136) in a case study of Barcelona hotel reviews, “even consumers who are fluent in more than one language expressly state that the use of their mother tongue influences their perceptions of service quality (Holmqvist 2011) and will have a positive influence on their evaluation of the service and loyalty (Holmqvist and Grönroos 2012). During the trip, communicating in their native language with tourists who have little knowledge of the local language helps them to feel more relaxed and welcome, especially when problems arise (Cocoa and Turner 1997; Russell and Leslie 2002)”.

The variety of situational contexts in tourism communication, often in relation to the diversity of experiences sought by the various categories of tourists, further emphasise the complexity of tourist communication, which has to be managed in the best possible way by both public policy bodies and businesses. It is therefore a paradox that translation studies only recently started to systematically analyse tourism discourse in the context of specialised translation. Isabel Durán Muñoz points out two possible reasons for this:

Tourism discourse has recently started to be investigated from a linguistic perspective and also to be considered as a specialized translation. This is basically due to two main features: on the one hand, its interdisciplinarity, that is, this field is highly influenced by other disciplines (geography, economics, history, and sport, among others) and employs their terminology very frequently; and on the other hand, its level of specialization, i.e., the recipients of tourist texts are usually non-specialists in the field, what makes the discourse to be close to general language and then, very low specialized. These features have provoked that the tourist discourse had not been considered as a specialized discourse until very recently (2011, 32).

The importance of the tourism sector for Mediterranean countries and in particular for Greece and Cyprus, the key position of multilingual communication and translation and the possible contribution of Machine Translation and especially the EU’s eTranslation, were the starting point for a consultation between me, representing the Aristotle University of Thessaloniki and its EMT programme, the Greek Language Department of the European Commission’s Directorate-General for Translation (DGT), and the DGT’s Field Officers in Athens and Nicosia. Our discussion focused on the EU’s wider effort to create a single European Digital Market (“A Europe fit for the Digital Age”), with sustainability as its underlying principle, also through the continuous development of the eTranslation system, which is provided free of charge to public administrations and SMEs in all Member States, as well as on MT’s potential contribution to the development of the tourism sector in Greece and Cyprus.

Two points were of particular concern to us. First, the fact that tourism activities had all but stopped due to the pandemic and that the future could look very different from what we have been accustomed to. However, we were convinced that such changes would not alter the core of tourism intercultural communication, despite any differences in scale and orientation. The second point of concern was the actual role of MT in intercultural communication, which is hotly debated among translators (see ATA 2018) and translation researchers. Τranslation researchers, who have been mostly studying MT and its pros and cons in the context of specialised translation, e.g. law (Wiesmann 2019), have recently broadened the scope of their research to examine new contexts, such as migration (Macías, Ramos, & Rico, 2020) and even literary translation (Toral 2020). On the other hand, the quality of MT and its assessment continues to be discussed often alongside post-editing, and time and effort in its context (Läubli et al. 2019; Toledo Báez 2018; García 2012).

Taking into account these aspects, we decided to organise a seminar on the use of eTranslation, its advantages and disadvantages, aimed at professionals and public authorities of the tourism sector in Greece and Cyprus. That means that we focused on the use of eTranslation by non-translators, with the aim of showing them how to use MT in the most effective way possible in specific communication situations and pointing out other communication situations where translation has to meet the highest quality standards, meaning that the use of MT is inadvisable. The seminar was thus aimed to train people in using eTranslation in possible situations where translators most often are not or cannot be involved. Of course, given the target-group of the seminar, the discussion on quality couldn’t be expressed in theoretical terms, e.g. of equivalence in semantic, pragmatic and textual level, according to House, who adds, in its revisited model, the important parameter of cultural filtering (2014).

A dedicated webpage was created to manage registrations and promote the event on social media. The seminar took place online on 3 December 2020, and was attended by around 70 people from Greece and Cyprus, including representatives of government bodies, research centres, professional associations and businesses of the tourism sector. Translators remained central to this seminar, as experts in multilingual and multicultural communication, who must be consulted in various contexts of the tourism industry and their work is of primary importance. For this reason, we invited John O’Shea, head of FIT Europe’s reflection group on MT, to the panel of speakers, who presented FIT Europe’s view on the pressing need for quality translation in many areas of the tourism sector.

Markus Foti, the head of the DGT’s MT division, presented the rationale behind eTranslation and the way it works. This was followed by two hands-on seminars (conducted by me and Dr. Kyriaki Kourouni, both tutors on the Aristotle University of Thessaloniki’s EMT programme) with specific scenarios highlighting the potential and the weaknesses of eTranslation. Unfortunately, the seminar was not filmed, as many participants did not give their consent, but all participants received the material of the hands-on seminars.

The aim of the hands-on seminars was to show what eTranslation can and cannot do in tourist communication, focusing firstly on the two parameters of human evaluation of MT, accuracy and fluency, as described in the MQM usage guidelines: “Accuracy addresses the extent to which the target text accurately renders the meaning of the source text […] Fluency relates to the monolingual qualities of the source or target text, relative to agreed-upon specifications, but independent of relationship between source and target.” (Burchard & Lommel 2014, 6; see also Han & Wong 2016; Dorr, Snover, & Madnani 2009); and secondly on the need respectively of accuracy/adequacy and fluency in concrete, often culturally bounded contexts in tourism. Lastly, the seminar aimed to introduce the participants to the inner logic and functioning of eTranslation, so that they are able to adapt their expectations accordingly and, by contributing relevant resources, help enhance its performance. It was stressed from the beginning that the examples used referred exclusively to: (a) communication situations in tourism, where usually no translators are used; and (b) general approaches to draft information, which can be though extremely useful for strategic purposes.

In my seminar, I attempted, firstly, through some simple examples of oral, or written  communication (e.g. seasons’ greetings) to point out that it is sometimes difficult for MT in general and eTranslation in particular to manage effectively even simple cultural elements or context, as can be seen in examples I to III –although it is true that Neural Machine Translation (NMT) deals much better with realia and culture:

Example I

El Το Υπουργείο Τουρισμού σας εύχεται χρόνια πολλά και ευτυχισμένος ο νέος χρόνος

En The Ministry of Tourism wishes you happy and happy New Year

Fr Le Ministère du Tourisme vous souhaite bonne et bonne année

In this very simple example, the system cannot translate accurately the Greek wish “χρόνια πολλά” (literally: “many years”, meaning: may you live long, an expression used for a variety of celebrations, such as religious holidays, birthdays, anniversaries etc.), due to its limited ability to render cultural equivalents –a problem that can be remediated by feeding the system with relevant resources.

Example II

El Το γραφείο μας σας εύχεται καλά Χριστούγεννα και ευτυχισμένο το νέο έτος

En Our office wishes you a Merry Christmas and Happy New Year

Fr Notre bureau vous souhaite un joyeux Noël et une bonne année

The system, unlike a translator, cannot distinguish the type of “office” if this is not explicitly marked. However, even if it is explicitly marked, the resulting literal translation may refer to a completely different reality, as is shown in the following example.

Example III

El Το τουριστικό γραφείο μας σας εύχεται καλά Χριστούγεννα και ευτυχισμένο το νέο έτος

En Our tourist office wishes you a Merry Christmas and Happy New Year

Fr Notre bureau de tourisme vous souhaite un joyeux Noël et une bonne année

The literal translation of the term “τουριστικό γραφείο” (which means “travel agency” in Greek) into “tourist office” is incorrect, as the latter refers to a public tourist information/service unit and not to a private company. A professional translator, perceiving immediately the context, would have translated the term correctly.

Example IV

El Το Γραφείο Tαξιδίων μας σας εύχεται καλά Xριστούγεννα και ευτυχισμένο το νέο έτος

En Our travel agency wishes you a Merry Christmas and Happy New Year

Fr Notre agence de voyages vous souhaite un joyeux Noël et une bonne année

Only if we provide the system with an absolutely clear and culturally neutral text as in the example IV, will we receive a satisfactory translation. Of course, we did not take into account the cases of non-Christian countries and clients, but used concrete examples to highlight the complexity of language even in relatively simple contexts, such as those of seasons’ greetings, and, above all, the scope of the communication: seasons’ greetings addressed to clients and partners, as public communication, have to be translated with both accuracy/adequacy and fluency. Therefore eTranslation’s use needs to meet concrete prerequisites if it is to be helpful.

After this rather disappointing but also enlightening start for the seminar’s participants, I continued with situations where the system can really be particularly useful to professionals and public authorities: e.g. for the translation of multilingual reviews on social media and dedicated websites, on the basis of which they can adapt their policy and visibility actions. In this particular case, eTranslation can be used to get the general gist of reviews or of website content from existing and, even more, from emerging markets. In these cases, eTranslation can be used to get a more accurate translation, compared to the one from other systems, as illustrated by the following example from Romanian into Greek.

Ro Nu recomand

5,0 A apreciat· Doar panorama ce se poate admira din balcon.

Nu a apreciat· Mobilier vechi, patul foarte neconfortabil, usa balconului din lemn si foarte zgomotoasa.

Nu as recomanda sejur aici.

Chicineta vai de ea…

El Δεν το συνιστώ.

5.0 Εκτίμησε· Μόνο τη θέα που μπορείτε να θαυμάσετε από το μπαλκόνι.

Δεν εκτίμησε· Παλιά έπιπλα, πολύ άβολο κρεβάτι, ξύλινη μπαλκονόπορτα και πολύ θορυβώδη.

Δεν θα συνιστούσα να μείνετε εδώ.

Το κουζινάκι της αλίμονο…

The translation of the comment on the kitchen by Google Translate («Η μικρή κουζίνα πηγαίνει από αυτήν», literally: the little kitchen goes by itself), does not make any sense, whereas eTranslation offers an inept translation, which can however be understood.

Based on more examples, I pointed out that, when we cannot check the translation because we do not speak the language, and in these exactly cases eTranslation can obviously be useful, we have however to decide beforehand whether a communication with possible blunders is more important than the absence of communication. Or, in other words, if communication is absolutely necessary, even with some blunders, while, when it comes to public communication, it is always necessary to resort to translators.

For example, eTranslation can be particularly useful to a hotel’s reservation desk, especially when communicating with customers prior to their arrival, for the translation of both customer requests and the hotel’s responses. This kind of communication is rather limited and standardised. While most websites are translated into many different languages and have an extranet for the communication of businesses with customers, the latter often tend to write in their own language. In such cases, eTranslation can be useful, as the relevant topics tend to be rather concrete: for example a celebration during the stay, a booking at restaurant X on day X etc. It is easy to train employees on the system’s specificities so that they can respond to such requests.

It was shown that eTranslation can also be useful in obtaining a general idea of the content of a contractual text, such as the sale contract of a holiday package translated from Greek into French, and of a legal text, such as the Romanian law amendments on tourism, also translated in Greek. However, these translations are by no means official, nor can they be used to conclude an agreement. Finally, we presented examples of gleaning information from foreign websites on Greece’s image as a travel destination, with reference to a Brazilian site with content written in Brazilian Portuguese with no translation into other languages; and also of the translation of informative texts concerning Greece and Cyprus, that can form the basis for new texts promoting these countries in foreign markets.

From the webinar it became clear that, despite its limitations, eTranslation can be helpful in cases where communication is essential or urgent, or when one needs to get the general gist of a text or collect information in order to form a policy or strategy. It can support specific situations of informal communication, as in the case of hotels for example, facilitating the personalised management of clients, while always taking into account and factoring in possible communication blunders. It can also support strategic watch, i.e. the monitoring of tourism developments in many languages, thus allowing public bodies and businesses to shape their strategy and approaches based on diverse, multilingual data. However, under no circumstances can it be used in public and official communication, where only translators can provide high-quality, efficient translations, which take into account the various aspects of communication, especially cultural specificities that are necessary for effective communication in a variety of contexts..

The seminar received overwhelmingly positive reviews and we are currently working on its follow-up, hoping that we will soon have some new elements that can give directions to the practical use of eTranslation in tourism and other sectors. The system’s results will certainly continue to improve, as long as it is constantly fed with relevant resources and we hope that participants have taken note of it and will provide tourist language resources (ELRC-share) to support its development.

References

Burchardt A. & Lommel, A. (2014). Guide to selecting MQM issues for the MT Evaluation Metric. In Practical Guidelines for the Use of MQM in Scientific Research on Translation Quality, http://www.qt21.eu/downloads/MQM-usage-guidelines.pdf.

Dorr, B., Snover, M. & Madnani, N. (2009). Part 5: Machine translation evaluation. In Bonnie Dorr (Ed.), DARPA GALE program report, https://www.cs.cmu.edu/~alavie/papers/GALE-book-Ch5.pdf.

Durán Muñoz, I. (2011). Tourist translations as a mediation tool: misunderstandings and difficulties. Cadernos de Traducão, 27, 29-49. DOI: 10.5007/2175-7968.2011v1n27p29.

FIT Position Paper on Machine Translation, https://www.fit-ift.org/fit-position-paper-on-machine-translation.

García, I. (2012). A Brief History of Postediting and of Research in Postediting. Anglo Saxonica, 3(3), 291-310, http://ulices.letras.ulisboa.pt/wp-content/uploads/2016/07/anglosaxonica-iii-03-1.pdf.

Han L. & Wong D. F. (2016). Machine translation evaluation: A survey. Computing Research Repository (CoRR, abs/1605.04515).

House, J. (2014). Translation Quality Assessment. Past and Present. London/New York: Routledge.

Läubli, S., Amrhein, Ch., Düggelin, P., Gonzalez, B., Zwahlen, A. & Volk, M. (2019). Post-editing Productivity with Neural Machine Translation: An Empirical Assessment of Speed and Quality in the Banking and Finance Domain. In Proceedings of Machine Translation Summit XVII Volume 1: Research Track. Dublin: European Association for Machine Translation, https://arxiv.org/abs/1906.01685.  

Liu, X., Mehraliyev, F., Liu, C., & Schuckert, M. (2020). The roles of social media in tourists’ choices of travel components. Tourist Studies, 20(1), 27–48. DOI: 10.1177/1468797619873107.

Macías, L., Ramos, M. & Rico, C. (2020). Study on the Usefulness of Machine Translation in the Migratory Context: Analysis of Translators’ Perceptions. Open Linguistics, 6(1), 68-76. DOI: 10.1515/opli-2020-0004.

Pablo de Carlos, Elisa Alén, Ana Pérez-González & Beatriz Figueroa (2019) Cultural differences, language attitudes and tourist satisfaction: a study in the Barcelona hotel sector. Journal of Multilingual and Multicultural Development, 40(2,) 133-147, DOI: 10.1080/01434632.2018.1493114.

Toledo Báez, M. C. (2018). Machine Translation and Post-editing: Impact of Training and Directionality on Quality and Productivity. Revista Tradumàtica, 16 24-34. DOI: 10.5565/rev/tradumatica.215.

Toral, A. (2020). Machine Translation of Novels in the Age of Transformer. In  Jörg Porsiel (Ed.), Maschinelle Übersetzung für Übersetzungsprofis (pp. 276-295). Berlin: BDÜ Fachverlag, https://arxiv.org/abs/2011.14979.

UNWTO (2020). Tourism Highlights, https://www.e-unwto.org/doi/book/10.18111/9789284422456.       

UNWTO INTERNATIONAL TOURISM AND COVID-19 https://www.unwto.org/international-tourism-and-covid-19.

Wiesmann, E. (2019). Machine Translation in the Field of Law: A Study of the Translation of Italian Legal Texts into German. Comparative Legilinguistics, 37(1), 117-153. DOI: 10.14746/cl.2019.37.4.

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.

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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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