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Translators without Borders announces winners in the 2018 Access to Knowledge Awards

Source: Translators without Borders
Story flagged by: Jared Tabor

The Access to Knowledge Awards are presented annually to top contributors supporting the Translators without Borders mission. These award winners are leading the effort to ensure vulnerable people have access to vital knowledge in local languages. These awards are the preeminent honor given by Translators without Borders to those from the humanitarian, development and language sectors working in the field of communications in the right language.

The awards, which honor volunteers, donors, and non-profit partners, are given within six categories: Right to Knowledge Award for a translator or translation company who has translated humanitarian content with Translators without Borders; Excellence Award for an individual who has volunteered ‘above and beyond’ in supporting Translators without Borders; Empowerment Award for an individual or organization who has helped train or mentor new translators; Communicator of the Year for an individual who builds awareness of the need to increase access to knowledge; Humanitarian Communicator for a non-profit that exemplifies increased access to information in the right language; and Donor Award for an individual or organization that has significantly contributed to the financial health of Translators without Borders.

Congratulations to member Gladis Audi, on the French Translation Team receiving the Empowerment Award, and to Ashutosh Mitra, Monika Saraf and Bhashna Gupta, receiving honorable mention as part of the eCancer Hindi team.

See the full awards announcement >>

PayPal announces update to its Terms and Conditions

Source: PayPal
Story flagged by: fklingenschmid

Hello everybody,

I just got notified, that PayPal is changing its Tems & Conditions on May 25th 2018.

You should give it 5 minutes and check the conditions concerning your country of residence and also which countries are the ones, you get the most transactions from. Mind, that there’s a huge difference if payments are based on bank accounts or credit cards.

I e.g. just realized, that it makes a big financially difference, that my account is registered in Germany, not Austria, and have to make the necessary changes soon.

How do you handle your PayPal fees anyway? Are you simply accepting that loss of money or do you add the costs in your invoices, so the client has to pay them?

Have a great and productive week,


Wordfast releases Wordfast Pro 5.4 and Wordfast Anywhere 5.0

Source: Wordfast
Story flagged by: Jared Tabor

Wordfast has released version 5.4 of its platform independent desktop tool, Wordfast Pro. Notable features and improvements include Adaptive Transcheck, a new segment changes report format, a new feedback proxy tool, and the ability to connect to Wordfast Anywhere TMs and glossaries. This latest feature puts the power of server-based TMs and glossaries into the hands of desktop users for free. Please see the release notes page for more details.

Wordfast also recently released Wordfast Anywhere 5.0 which includes a localized user interface in French and Spanish. The UI is ready to be translated to other languages with a collaborative translation page accessible through a user’s profile.

Wordfast will be showcasing the interconnectivity of Wordfast Pro and Wordfast Anywhere during its 4th annual user conference – Wordfast Forward – to take place on June 1-2, 2018 in Cascais, Portugal.

Microsoft claims MT system “achieved human parity” on test data

Source: Techcrunch
Story flagged by: Ambrose Li

“A team of Microsoft researchers announced on Wednesday they’ve created the first machine translation system that’s capable of translating news articles from Chinese to English with the same accuracy as a person. The company says it’s tested the system repeatedly on a sample of around 2,000 sentences from various online newspapers, comparing the result to a person’s translation in the process – and even hiring outside bilingual language consultants to further verify the machine’s accuracy.”

Source: Techcrunch

Participate online in Elia Together 2018 (free for Plus subscribers)

By: Jared Tabor

As you may have already heard, the European language industry association (Elia) and have teamed up to broadcast this year’s event, Together 2018Together is an annual two-day event from Elia, where language service companies and independent professionals convene for open dialogue on industry trends, to learn mutually-relevant new approaches, to update technical skills and, ultimately, develop lasting relationships to serve their end clients better. This year, the event will be held on February 22nd and 23rd.

If you are a Plus subscriber, you will have access to the broadcast and recordings from this year’s event for free.

All you have to do is:

  1. Make sure you are logged in to your account.
  2. Go to at (also found under the “Member activities” section of the site menu).
  3. Enjoy.

Elia Together 2018

This event has been approved for up to 7 ATA Continuing Education points. Important: in order to earn CE points, you must click the “Get credentialed” button on the timer above the video player on

Slovakia parliament passes amendment covering reporting of mistakes and payment terms for translators and interpreters

Source: Slator
Story flagged by: Jared Tabor

Slovakia’s parliament passed an amendment on February 6, 2018 to govern how courts, prosecution bodies or other public bodies (public authorities) manage the use of authorised experts, translators and interpreters.

This new law, proposed by the Justice Ministry, imposes on the public authorities a new ‘information duty’. This includes reporting the faults of experts, translators and interpreters whom they have used to the Justice Ministry. The Ministry would then decide on the punishment. No further details on the kind of punishment were available.

Such faults include “refusal to execute a job, causing delays or making a professional mistake”. If punished, the details of the incident would be published on the Justice Ministry’s website.

However, the amendment allows for experts, translators and interpreters the chance to “suspend their activities based on their own request, but only three times at the most, with the maximum time span being two years”.

On the flip side, the new law also sought to benefit these group of professionals. For instance, public authorities are now required to settle linguists’ bills in a timely manner.

Peter Zoricak, CEO of Tetras Translations, told Slator that this could be because “authorities did not pay on time and it caused a lot of translators and/or experts to refuse to work for them”.

Also experts, interpreters and translators will be allowed to use the knowledge gained through their work for public authorities for their scientific, research or teaching activities.

Slator also reached out to Jakub Absolon, owner and CEO of, who welcomed the new law.

“I think these provisions will increase the transparency of the process and define clearly the responsibilities of both translators and public authorities. It helps to better protect honest, professional sworn translators and also the recipient of such services (citizens).”

Zoricak also agreed that the new law “seems positive for the professionals”. The amendment will be effective as of July 1, 2018.

The reality of the language services sector in 2018 and beyond

Source: Common Sense Advisory
Story flagged by: Jared Tabor

Business is looking good in the language sector. CSA Research’s business confidence survey of the CEOs of the largest language service providers found 2017 to be a growth year, and respondents optimistically entered 2018. Sector revenue and language output continue to rise as the content and code that power economies are becoming more global. Our annual survey will give a more complete picture of the market as we collect and analyze the data.

This optimism plays out against a backdrop of concerns about the future of language services, on both the demand and supply side of the market. Buyers worry about the need to process ever-growing content volumes into more language pairs – but with relatively stable budgets. Meanwhile, they must deal with their management’s expectations that Amazon and Google Translate will take care of that pesky language problem once and for all – and with less complexity and at a lower cost.

On the supply side, LSPs express fundamental anxiety about the sustainability of their business models. We hear concerns across all tiers of the language service market:

  • Automation and procurement specialists marginalize small providers. These LSPs wonder where they fit in the market and how they’ll survive. They worry about sales, staffing, and the need for more – and competition with – increasingly powerful technology. Will their translation work be replaced by a bunch of Amazon servers? Will their project management value be replaced by bots? Further, they must also contend with commoditizing forces beyond their control such as distant procurement functions created when their clients are acquired by global behemoths.
  • Market forces squeeze mid-sized companies from both ends. Further up the value chain, medium-sized companies face niche specialists on one side, generalist multi-language vendors on the other, and those same procurement challenges. These mid-tier firms strategize about how they can scale up more quickly and compete against the economies of scale that the largest LSPs bring to bear. They plan growth both organically and by strategic liaisons or acquisitions.
  • The largest providers scramble for scale. At the top of the pyramid, the largest LSPs position themselves to get even bigger, scale to their clients’ fondest dreams for global content, strive for organic growth, and engage in pitched battles to buy a shrinking pool of mid-sized acquisitions. They’re also investing more in building their own technology as they climb to the higher stages of LSP Metrix maturity.

In conversation after conversation, we witness debates about technology. On one side, advocates pitch the importance of advanced technology to growth and scalability. On the other, naysayers anxiously await the swarms of AI-driven language bots and machine learning that will surely exterminate their companies. Their concern extends beyond machine translation to project management − will simple rule-based automation and deep machine learning conspire to eliminate the last humans on the language shop floor? CSA Research characterizes this angst as techno-phobia − or maybe more precisely, phobAI or its homophone FOBAI, the fear of being AI’d out of existence.

But we contend that FOBAI is a symptom of a bigger problem – mistaken identity. LSPs concerned about having automation wipe them out think they’re in the translation business. They’re not. Language service providers are business process outsourcers (BPOs), traditionally tasked with the job of rendering one language into another but now on the cusp of a much broader role managing more of the content assets for their digitizing clients. While conventional agencies still quibble about how many pennies they charge to translate a word, their buyers are far more interested in bigger content issues tied to their digital transformation. These clients are bringing all their information online, optimizing it, adapting and adopting technology to manage it, and making those assets available across the enterprise. This digitization has forced them to re-think internal systems and processes, pry open databases and content management systems, and educate their staff and suppliers in this new model.

How will their clients’ digitization strategies transform the LSPs supplying them?


European Language Resources Association announces new catalog of Language Resources

Source: ELRA
Story flagged by: Jared Tabor

ELRA is happy to release a new version of its Catalogue of Language Resources publicly.

Completely redesigned, with a new interface and an improved navigation, the new Catalogue allows visitors an easier access to the 1075 Language Resources (LRs) and their corresponding description. Among the new features, the Catalogue now offers an extended metadata to describe the LRs, a refined search on the Catalogue data for finding more specific information using criteria such as language, resource or media type, license, etc.

Currently, LRs can be selected, and placed in a cart from where the user can send a request for quotation to initiate the order. When logging in, the user selects LRs and obtains distribution details (licensing information, prices) depending on his/her user status: ELRA member/Non-member, Research vs Commercial organization. The full e-commerce integration will be completed at a later stage.

More functionalities pertaining to the ELRA Catalogue, including the ISLRN automatic submission and the e-licensing module (automatic filling in and electronic signature), will be developed and integrated.

Please visit this new version of the Catalogue here:

*** About ELRA ***

The European Language Resources Association (ELRA) is a non-profit making organisation founded by the European Commission in 1995, with the mission of providing a clearing house for language resources and promoting Human Language Technologies (HLT).

To find out more about ELRA, please visit:

[Podcast] Ethics in machine translation

Source: Moravia
Story flagged by: Jared Tabor

We’re in a localization and globalization market now where more words are translated every day through machine translation than what was translated in the entire human language corpus in the past.

Not only does such a massive amount of machine translation radically change the role of human translators, it also creates a whole new range of issues that impact the translation and globalization paradigm itself.

And one of the most important issues is ethics.

In an era when entire translations or at least substantial parts of them are often done by machine instead of by professional translators, what does it mean to provide “services” from an ethical perspective as far as translators and LSPs are concerned?

In this week’s episode of Globally Speaking, our hosts Renato Beninatto and M.W. Stevens discuss this very important issue that affects everyone involved in the language industry—both providers and buyers of translation services alike.

Major topics include:

  • What needs to be disclosed to buyers and what doesn’t?
  • Are language professionals now selling a product or a service?
  • When are translators in breach of a client contract by using machine translation, and when are they not?
  • Why machine translation is unlikely to ever replace the need for professionally trained translators.
  • How do LSPs charge for projects in which machine translation plays a major role?

Listen to the podcast >>

[Podcast] Unlocking New Markets with Data and Machine Learning, as told by Smartling’s CEO

Source: Deciding by Data
Story flagged by: Jared Tabor

Jack Welde helps companies make more money by speaking their customers’ language — literally. Welde is the Co-Founder and CEO of Smartling, a disruptive translation services company that uses a combination of human and machine translation to help companies enter new markets faster.

Welde says in the interview that consumers are 75 percent more likely to convert when they are being sold to in their native language — even if they are comfortable with the language they’re reading. Smartling measures the accuracy of translations with data, as well as the translations’ effectiveness in reaching new customers.

Read the interview or listen to the podcast >>

[Podcast] Finding translation clients in 2018 – Interview with Sherif Abuzid, episode 159 of Marketing Tips for Translators

Source: Marketing Tips for Translators
Story flagged by: Jared Tabor

In this episode we are talking about what methods work to find translation clients in 2018. With me I have a translation company owner and translator, Sherif Abuzid, who is sharing his best tips for finding clients. These are suggestions based on his experience. Pick the ones that work for your situation, depending on experience and preference, but also depending on your location.

Important things mentioned in this episode:

  • Change in how we find and contact clients during these last 10 years
  • What resources for finding clients we should focus on
  • How we should contact new clients
  • Differences in marketing if you are a newer translator vs a more experienced one

Read more and download/listen to the podcast >>

Tools and Translators: Interview with Jost Zetzsche

Source: Moravia
Story flagged by: Jared Tabor

By Vijayalaxmi Hegde

By and large, those of us in the localization industry are multi-cultural and multilingual, traveling the world, celebrating the diversity and power of language. We are interested in languages, culture, and language technology, and how they influence and shape our lives. Many of us also cross over from linguistics and language to the technical side of things.

Jost Zetzsche, a localization professional with nearly 20 years of experience, is a thought leader in these areas. He put his expertise into his latest book, Translation Matters. Comprised of 81 essays collected over the past 15 years, Jost’s book describes a world of translation where technology changes rapidly, but where the translator remains the central figure, ever-savvier in using the tools of the trade.

I had the chance to sit down with him and talk about these ideas.

Viju: One very hot topic on the minds of translators today is Machine Translation (MT).

Jost: In part, my book deals with the identity of translators at a time when MT has clearly become important. It’s critical as translators to define who we are and, on the basis of that self-perception, understand our role in the world and our role in relation to things like machine translation. That’s what the book is about to a certain extent.

The way we translators usually approach MT is either we reject it and say, “I don’t want to deal with machine translation,” or we say, “Okay, then I guess I have to do what I’m told to do with machine translation.” And that’s typically post-editing. And while in some situations, post-editing is the right choice, more often than not there are better ways of dealing with machine translation than to not use it at all or only post-edit. For example, translators can greatly benefit from data that is being suggested by machine translation engines without actually “post-editing” complete segments.

Viju: When I think about MT, I also think about another industry hot topic: AI. What are your thoughts on that?

Jost: I just read an article that talked about artificial intelligence, and it said that translators are kind of the canary in the coal mine. If translators become extinct, then we have truly reached a point of no return, where everything has completely changed, where everything has been turned upside down, and where artificial intelligence has essentially taken over.

Translators have a very secure job for a long time to come. If their job becomes insecure, if artificial intelligence, machine translation, is truly able to take over from translators, society will have changed so much that we will not recognize it anymore. Then, essentially, we’re all out of a job. We’ll have to redefine what it means to be productive, what it means to be a human being, what it means to work in the industry, etc.

At that time, there will be what Ray Kurzweil and others are calling this moment of singularity where we don’t need to work in the kinds of professions that we work in today. But, I think translators will be among the last to go.

What translators do is very close to what it means to be human: to be able to communicate in a complex and multi-layered manner. That’s something that computers can’t do unless we reach that point of singularity.

But don’t misunderstand me—it’s not as if we’re not impacted. But our job is NOT being taken away by it.

Viju: What happens to a translator who’s not inclined to learn about the whole range of tools available? Is there space for such a translator anymore?

Jost: Absolutely. You don’t have to be a tech geek to be a translator. My background is the opposite of technical. But I find joy in making technology work for me in a way that is productive and thinking of new ways of making it even more productive. And I think that’s something that translators should have. So that’s not geeky—it’s just looking at what’s out there and finding the right tools that work for you. I don’t think translators need to know all the tools. They just have to have an idea of what is out there and then make intelligent decisions on which tools to use.


What’s new in the second edition of the ITC Guidelines for Adapting Tests

Source: Responsive Translation
Story flagged by: Jared Tabor

The International Test Commission’s “ITC Guidelines for Translating and Adapting Tests” is a document that informs and directs our work adapting tests for different linguistic and cultural contexts. As a translation agency that specializes in high-stakes projects, we regularly translate and adapt tests and assessments in fields like education, health and human resources.

The wisdom of the guidelines’ first edition was an important part of our previous adaptations’ success. However, test development and adaptation continue to evolve as technology, practices and applications change. The second edition of the “ITC Guidelines for Translating and Adapting Tests” incorporates these new considerations and will guide our adaptation work going forward. But where did these guidelines come from and what exactly is in the second edition?

The ITC and the Original Guidelines

The International Test Commission is an association made up of test publishers, psychological associations and other organizations dedicated “to promoting effective testing and assessment policies and to the proper development, evaluation and uses of educational and psychological instruments.”

In 1992, the ITC began work on a set of guidelines for translating and adapting tests. A committee was formed and the guidelines were drafted and field tested.

The ITC formally adopted the “ITC Guidelines for Translating and Adapting Tests” in 2005 and published the first edition in its final form online in 2008. But their work was not done.

From 2005 to 2015, members of a second ITC committee, formally convened in 2007, worked to produce the second edition, which was published online in 2017 and is the subject of our attention today.

What’s in the Guidelines

The first edition contained 22 guidelines divided into four areas: Context, Test Development and Adaptation, Administration and Documentation/Score Interpretation.

The second edition, however, contains a set of 18 guidelines. Here each guideline is given and then immediately followed by an explanation as well as some suggestions for putting it into practice. The guidelines are divided into six areas: Pre-Condition, Test Development, Confirmation, Administration, Score Scales and Interpretation, and Documentation. The publication also includes a checklist for implementing the guidelines in an adaptation project and a glossary of terms.

The first edition was instrumental in providing a best practice framework for translating and adapting tests destined for different linguistic and cultural contexts. However, we find that the second edition is more practical, giving readers better guidance for implementation.

You can view the complete second edition of the “ITC Guidelines for Translating and Adapting Tests” here.


Paula Ribeiro on APTRAD’s 2nd international conference (May 17 – 19)

Source: Translator T.O.
Story flagged by: Jared Tabor

Translation challenges over the next decade and how to address them

Today’s guest post was written by Paula Ribeiro – president and co-founder of the Portuguese Association of Translators and Interpreters (APTRAD). Paula is a long-time member and part of the Certified PRO Network. APTRAD will be holding its second international conference on May 17th, 18th and 19th in Porto, Portugal.

APTRAD, the Portuguese Association of Translators and Interpreters, was established in February 2015 by a group of freelance professionals in response to a perceived need for a modern, creative and innovative approach in order to achieve greater cohesion and exchange of information at a national level within the profession. After almost one year of hard work we are proud of achieving some of the important goals we initially set.

APTRAD’s motto – Interpreting the present to translate the future – reflects the Association’s aim to promote and foster the growth of its professional members, and to support the integration as professionals of all future translators and interpreters into the market.

Pursuing this thought, APTRAD is to hold its 2nd International Conference from 17 to 19 May 2018 in Porto, Portugal – a bilingual event full of opportunities to explore, learn, share, and of course network! The conference, based on the theme Translation challenges over the next decade and how to address them, will explore the challenges of a professional freelance translator and/or interpreter during the next decade and how to address and overcome them.

As in 2016, where we welcomed more than 300 participants from all over the world, we are all trying to turn this event into a big party for translators, interpreters and linguists in general joining us in our beloved hometown – Porto.

The organization of this event becomes much easier with the valuable help of our partners, in which is included as an essential reference in the career of so many professionals. Thank you for your support!

Feel free to visit our website at and more specifically the conference website and drop us a line if you need help or some extra information about the event!

And if you are still considering, see what participants had to say about APTRAD’s 1st International Conference in 2016 here.

Also, and because an event is just not work time, be sure to check out the amazing fringe events awaiting you in Porto.

See you this May! We promise you an unforgettable event and lots of fun!

For more information:

APTRAD website:

APRTRAD conference:

Facebook event page:

The Norwegian Olympic team was sent 15,000 eggs because of Google Translate error?

Source: Chicago Sun Times
Story flagged by: Jared Tabor

I can’t tell how much of this is a GT error, or if someone just accidentally added a zero. Either way, that’s a lot of omelettes. — Jared

A Google Translate error resulted in Norway’s Olympic Team receiving 15,000 eggs.

Norway’s Olympic Team chefs were compiling a grocery list for its Olympic athletes competing at the 2018 Winter Games in South Korea. Due to the language barrier, the chefs used Google Translate to help them order from a Korean grocery store.

But when truckloads full of eggs showed up at Norway’s camp shortly after the transaction, the chefs quickly realized there was an error in their translation through Google.

View image on Twitter

Rather than ordering 1,500 eggs, the chefs ordered 15,000 — that’s equivalent to 1,250 cartons of 12.

“There was literally no end to the delivery. Absolutely unbelievable,” chef Ståle Johansen told Norway’s Aftenposten.

Fortunately, the chefs will be able to return the extra 13,500 eggs they received.

Juvenes Translatores: announcing this year’s winners of the European Commission’s translation contest for secondary school students

Source: European Commission
Story flagged by: Jared Tabor

Congratulations to 28 talented young students for winning the 2017-2018 translation contest for schools ‘Juvenes Translatores’! The winners will come to Brussels on 10 April to collect their awards for the best translation submitted by their country.

The European Commission announced the winners of its annual translation contest ‘Juvenes Translatores on February 2nd. A total of 28 secondary school students, one from each Member State, will be invited to Brussels on 10 April to receive their trophies and diplomas from Commissioner Günther H. Oettinger, responsible for Budget and Human Resources.

“My congratulations on your achievement. Well done for taking on the challenge and proving your talents in all 24 EU languages. Learning languages is a skill that is vital for your careers and personal development. It is amazing to see so many talented young people. Multilingualism defines us as Europeans”, said Commissioner Günther H. Oettinger.

The contest continues to garner strong support and dedicated participation. This year, over 3300 students from across the European Union translated texts on the 60th anniversary of the European Union. They could choose from any of the 552 possible combinations between any two of the EU’s 24 official languages. Students sat the competition in 144 language combinations, including translating from Polish into Finnish, and from Czech into Greek. All winners chose to translate into their strongest language or mother tongue, as the staff translators in EU Institutions do.


The European Commission’s Directorate-General for Translation has been organising the Juvenes Translatores (Latin for ‘young translators‘) contest every year since 2007. Its aim is to promote language learning in schools and give young people a taste of what it is like to be a translator. It is open to 17-year-old secondary school students and takes place at the same time in all selected schools across the EU. The contest has inspired and encouraged some of the participants to pursue their languages at university level and to become professional translators.

Translation has been an integral part of the EU from the outset, and the subject of the very firstRegulationin 1958.

The winners of this year are:

Juvenes Translatores 2017-2018 winners

Country Winner Participants
language pair
School Number of schools Number of students
Austria Johanna Tösch, EN-DE BORG Birkfeld, Birkfeld 18 87
Belgium Audrey Lizin,
Athénée Royal de Huy, Huy 21 97
Bulgaria Яница Стойкова,
Профилирана езикова гимназия „Проф. д-р Асен Златаров“, Велико Търново 17 76
Croatia Ante Kuvačić, EN-HR Prirodoslovna tehnička škola – Split, Split 11 52
Cyprus Δάφνη Ρουμπά, EN-EL Λύκειο Αποστόλων Πέτρου και Παύλου, Λεμεσός 6 29
The Czech Republic Anna Kovárnová,
Gymnázium Jírovcova, České Budějovice 21 96
Denmark Sarina Ulrich, EN-DA Paderup Gymnasium, Randers 13 53
Estonia Laura Emily Rilanto, FI-ET Tartu Jaan Poska Gümnaasium, Tartu 6 30
Finland Sara Soimasuo, EN-FI Tammerkosken lukio, Tampere 13 54
France Irene Campillo Pinazo, ES-FR Lycée Saint-Sernin, Toulouse 74 333
Germany Rebekka Mattes, HU-DE Marienschule, Leverkusen 93 370
Greece Θεοδώρα Πλιάτσικα,
1ο Γενικό Λύκειο Τρικάλων, Τρίκαλα Θεσσαλίας 21 91
Hungary Emese Tóth,
Debreceni Csokonai Vitéz Mihály Gimnázium, Debrecen 21 98
Ireland Alex Burke,
Christian Brothers College, Cork 10 38
Italy Gianluca Brusa, FR-IT I.I.S. “Carlo Emilio Gadda”, Paderno Dugnano 73 352
Latvia Reinards Jānis Saulītis,
Saldus novada pašvaldības Druvas vidusskola, Saldus pagasts 8 38
Lithuania Uosis Nojus Galkevičius,
Alytaus Adolfo Ramanausko-Vanago gimnazija, Alytus 11 53
Luxembourg Julie Oé,
Athénée de Luxembourg, Luxembourg 3 12
Malta Andrè Mifsud, EN-MT St Aloysius College, Birkirkara 6 30
The Netherlands Maud Rinkes, NL-EN Stedelijk Gymnasium Haarlem, Haarlem 26 110
Poland Michał Martinez Dzedzej,
CXXII Liceum Ogólnokształcące im. Ignacego Domeyki, Warszawa 51 238
Portugal Catarina Rodrigues,
Colégio Internato dos Carvalhos, Pedroso-Carvalhos – V.N. Gaia 21 98
Romania Cosmin Ionuț Lazăr, FR-RO Colegiul Național „Costache Negri”, Galați 32 155
Slovakia Katarína Kráľová,
Piaristická spojená škola F. Hanáka – gymnázium, Prievidza 13 57
Slovenia Ana Šubic,
Škofijska klasična gimnazija, Ljubljana 8 39
Spain Pablo Villar Abeijón, EN-ES IES De Brión, A Coruña 54 263
Sweden August Falkman,
Tyska Skolan, Stockholm 20 87
The United Kingdom Daniel Farley, ES-EN The Manchester Grammar School, Manchester 73 312
Total 744 3 348

For more information:

Juvenes Translatores:

Five people arrested for translating copyrighted works without permission

Source: Slator
Story flagged by: Jared Tabor

Slator has previously covered a number of issues surrounding the Japanese video game localization market. There are pirate translator groups comprised of fans voluntarily localizing media without permission. Usually, these are titles not intended to be localized for overseas markets. Japanese companies strike back with Digital Millennium Copyright Act (DMCA) takedown notices—legal digital cease and desist notices.

Recently, actions against volunteer translators have escalated to arrests.

At the start of February, five Chinese nationals were arrested in Japan (secondary source in English) for translating manga and games. The five suspects were allegedly part of a large translating group that distributes Chinese-translated Japanese media online.

Specifics cited in news reports claim that two of the suspects are a 24-year-old female research student and a 25-year-old female graduate student. They were arrested for translating a manga series and character dialogues for a video game. Japanese police are looking into other translations of copyrighted works the suspects are liable for, as they are part of an online group that has allegedly translated over 15,000 manga items without authorization.

Reports say the suspects face up to 10 years in prison, fines worth up to JPY 10m (USD 91,900), or both, as well as the possibility of civil lawsuits and additional levies for damages and, of course, orders to delete files. Four of the five suspects are reportedly voluntarily cooperating with the investigation.


memoQ translation trend report 2018

By: Jared Tabor

The folks over at memoQ have put together a report on trends to watch in 2018. The subjects covered in this report include:

  • “The rise of the machine: AI, ML. MT and more”
  • “Convergence and connectivity”
  • “User experience”
  • “Tiptoeing on the cloud, working the web”
  • “Business”
  • “New media”
  • “Factory”

Check out the report at

The shallowness of Google Translate

Source: The Atlantic
Story flagged by: Jared Tabor

One Sunday, at one of our weekly salsa sessions, my friend Frank brought along a Danish guest. I knew Frank spoke Danish well, since his mother was Danish, and he, as a child, had lived in Denmark. As for his friend, her English was fluent, as is standard for Scandinavians. However, to my surprise, during the evening’s chitchat it emerged that the two friends habitually exchanged emails using Google Translate. Frank would write a message in English, then run it through Google Translate to produce a new text in Danish; conversely, she would write a message in Danish, then let Google Translate anglicize it. How odd! Why would two intelligent people, each of whom spoke the other’s language well, do this? My own experiences with machine-translation software had always led me to be highly skeptical about it. But my skepticism was clearly not shared by these two. Indeed, many thoughtful people are quite enamored of translation programs, finding little to criticize in them. This baffles me.

As a language lover and an impassioned translator, as a cognitive scientist and a lifelong admirer of the human mind’s subtlety, I have followed the attempts to mechanize translation for decades. When I first got interested in the subject, in the mid-1970s, I ran across a letter written in 1947 by the mathematician Warren Weaver, an early machine-translation advocate, to Norbert Wiener, a key figure in cybernetics, in which Weaver made this curious claim, today quite famous:

When I look at an article in Russian, I say, “This is really written in English, but it has been coded in some strange symbols. I will now proceed to decode.”

Some years later he offered a different viewpoint: “No reasonable person thinks that a machine translation can ever achieve elegance and style. Pushkin need not shudder.” Whew! Having devoted one unforgettably intense year of my life to translating Alexander Pushkin’s sparkling novel in verse Eugene Onegin into my native tongue (that is, having radically reworked that great Russian work into an English-language novel in verse), I find this remark of Weaver’s far more congenial than his earlier remark, which reveals a strangely simplistic view of language. Nonetheless, his 1947 view of translation-as-decoding became a credo that has long driven the field of machine translation.

Since those days, “translation engines” have gradually improved, and recently the use of so-called “deep neural nets” has even suggested to some observers (see “The Great AI Awakening” by Gideon Lewis-Kraus in The New York Times Magazine, and “Machine Translation: Beyond Babel” by Lane Greene in The Economist) that human translators may be an endangered species. In this scenario, human translators would become, within a few years, mere quality controllers and glitch fixers, rather than producers of fresh new text.

Such a development would cause a soul-shattering upheaval in my mental life. Although I fully understand the fascination of trying to get machines to translate well, I am not in the least eager to see human translators replaced by inanimate machines. Indeed, the idea frightens and revolts me. To my mind, translation is an incredibly subtle art that draws constantly on one’s many years of experience in life, and on one’s creative imagination. If, some “fine” day, human translators were to become relics of the past, my respect for the human mind would be profoundly shaken, and the shock would leave me reeling with terrible confusion and immense, permanent sadness.

Each time I read an article claiming that the guild of human translators will soon be forced to bow down before the terrible swift sword of some new technology, I feel the need to check the claims out myself, partly out of a sense of terror that this nightmare just might be around the corner, more hopefully out of a desire to reassure myself that it’s not just around the corner, and finally, out of my longstanding belief that it’s important to combat exaggerated claims about artificial intelligence. And so, after reading about how the old idea of artificial neural networks, recently adopted by a branch of Google called Google Brain, and now enhanced by “deep learning,” has resulted in a new kind of software that has allegedly revolutionized machine translation, I decided I had to check out the latest incarnation of Google Translate. Was it a game changer, as Deep Blue and AlphaGo were for the venerable games of chess and Go?

I learned that although the older version of Google Translate can handle a very large repertoire of languages, its new deep-learning incarnation at the time worked for just nine languages. (It’s now expanded to 96.)* Accordingly, I limited my explorations to English, French, German, and Chinese.

Before showing my findings, though, I should point out that an ambiguity in the adjective “deep” is being exploited here. When one hears that Google bought a company called DeepMind whose products have “deep neural networks” enhanced by “deep learning,” one cannot help taking the word “deep” to mean “profound,” and thus “powerful,” “insightful,” “wise.” And yet, the meaning of “deep” in this context comes simply from the fact that these neural networks have more layers (12, say) than do older networks, which might have only two or three. But does that sort of depth imply that whatever such a network does must be profound? Hardly. This is verbal spinmeistery.

I am very wary of Google Translate, especially given all the hype surrounding it. But despite my distaste, I recognize some astonishing facts about this bête noire of mine. It is accessible for free to anyone on earth, and will convert text in any of roughly 100 languages into text in any of the others. That is humbling. If I am proud to call myself “pi-lingual” (meaning the sum of all my fractional languages is a bit over 3, which is my lighthearted way of answering the question “How many languages do you speak?”), then how much prouder should Google Translate be, since it could call itself “bai-lingual” (“bai” being Mandarin for 100). To a mere pilingual, bailingualism is most impressive. Moreover, if I copy and paste a page of text in Language A into Google Translate, only moments will elapse before I get back a page filled with words in Language B. And this is happening all the time on screens all over the planet, in dozens of languages.

The practical utility of Google Translate and similar technologies is undeniable, and probably it’s a good thing overall, but there is still something deeply lacking in the approach, which is conveyed by a single word: understanding. Machine translation has never focused on understanding language. Instead, the field has always tried to “decode”—to get away without worrying about what understanding and meaning are. Could it in fact be that understanding isn’t needed in order to translate well? Could an entity, human or machine, do high-quality translation without paying attention to what language is all about? To shed some light on this question, I turn now to the experiments I made.

I began my explorations very humbly, using the following short remark, which, in a human mind, evokes a clear scenario:

In their house, everything comes in pairs. There’s his car and her car, his towels and her towels, and his library and hers.

The translation challenge seems straightforward, but in French (and other Romance languages), the words for “his” and “her” don’t agree in gender with the possessor, but with the item possessed. So here’s what Google Translate gave me:

Dans leur maison, tout vient en paires. Il y a sa voiture et sa voiture, ses serviettes et ses serviettes, sa bibliothèque et les siennes.

The program fell into my trap, not realizing, as any human reader would, that I was describing a couple, stressing that for each item he had, she had a similar one. For example, the deep-learning engine used the word “sa” for both “his car” and “her car,” so you can’t tell anything about either car-owner’s gender. Likewise, it used the genderless plural “ses” both for “his towels” and “her towels,” and in the last case of the two libraries, his and hers, it got thrown by the final “s” in “hers” and somehow decided that that “s” represented a plural (“les siennes”). Google Translate’s French sentence missed the whole point.

Next I translated the challenge phrase into French myself, in a way that did preserve the intended meaning. Here’s my French version:

Chez eux, ils ont tout en double. Il y a sa voiture à elle et sa voiture à lui, ses serviettes à elle et ses serviettes à lui, sa bibliothèque à elle et sa bibliothèque à lui.

The phrase “sa voiture à elle” spells out the idea “her car,” and similarly, “sa voiture à lui” can only be heard as meaning “his car.” At this point, I figured it would be trivial for Google Translate to carry my French translation back into English and get the English right on the money, but I was dead wrong. Here’s what it gave me:

At home, they have everything in double. There is his own car and his own car, his own towels and his own towels, his own library and his own library.

What?! Even with the input sentence screaming out the owners’ genders as loudly as possible, the translating machine ignored the screams and made everything masculine. Why did it throw the sentence’s most crucial information away?

We humans know all sorts of things about couples, houses, personal possessions, pride, rivalry, jealousy, privacy, and many other intangibles that lead to such quirks as a married couple having towels embroidered “his” and “hers.” Google Translate isn’t familiar with such situations. Google Translate isn’t familiar with situations, period. It’s familiar solely with strings composed of words composed of letters. It’s all about ultrarapid processing of pieces of text, not about thinking or imagining or remembering or understanding. It doesn’t even know that words stand for things. Let me hasten to say that a computer program certainly could, in principle, know what language is for, and could have ideas and memories and experiences, and could put them to use, but that’s not what Google Translate was designed to do. Such an ambition wasn’t even on its designers’ radar screens.

Well, I chuckled at these poor shows, relieved to see that we aren’t, after all, so close to replacing human translators by automata. But I still felt I should check the engine out more closely. After all, one swallow does not thirst quench.

Indeed, what about this freshly coined phrase “One swallow does not thirst quench” (alluding, of course, to “One swallow does not a summer make”)? I couldn’t resist trying it out; here’s what Google Translate flipped back at me: “Une hirondelle n’aspire pas la soif.” This is a grammatical French sentence, but it’s pretty hard to fathom. First it names a certain bird (“une hirondelle”—a swallow), then it says this bird is not inhaling or not sucking (“n’aspire pas”), and finally reveals that the neither-inhaled-nor-sucked item is thirst (“la soif”). Clearly Google Translate didn’t catch my meaning; it merely came out with a heap of bull. “Il sortait simplement avec un tas de taureau.” “He just went out with a pile of bulls.” “Il vient de sortir avec un tas de taureaux.” Please pardon my French—or rather, Google Translate’s pseudo-French.


Why translators should start thinking about how much their hour is worth

Source: Slator
Story flagged by: Jared Tabor

by Silvio Picinini

We translators may be on the verge of dealing with more math surrounding our beloved words. Until now, the number that mattered most has been word count, because that is how we are paid. And fuzzy matches, of course—that magic algorithm that calculates how much partial help (and payment) we get.

We consider a segment short, medium, or long based on its word count. However, machine translation (MT) offers different ideas about different lengths; even neural MT with all the widespread praise for fluency.

For segments of one or two words, there is little to no fluency. So is that where neural MT goes out the window? Maybe, or maybe not. We have to find out. Either way, all of sudden, segment word counts have become metrics indicative of whether MT will translate fluently. Food for thought: how many words is still short? What is medium? What is long?

Another number to consider is edit distance. It may be coming to a translation productivity tool near you. That is because we will increasingly want to know how much MT is helping us do our job, and the answer to that (or a part of the answer) is how many changes we make to the suggestions we receive.

If the MT is really awesome in a 30-word sentence, we smile, make two changes, and the edit distance is low. If the MT requires reordering the words and fixing brands that were inaccurately translated, then we are putting a lot more effort and the edit distance will reflect that.

As much as I love edit distance, it is just a comparison between one initial “image” of the sentence and the final “image” that we created. But then there is adaptive technology, that keeps changing the suggestions as we move. Working with adaptive technology, there isn’t really an initial “image” or “initial full sentence translation.” So, it is complicated.

Let’s explore some other numbers: what is the average number of words per sentence in our text?

If it is high—let’s say 16—it means longer and more fluent sentences, and maybe we should expect neural MT to lend us a hand with it. But if we are translating software strings or mobile content, life isn’t like that, is it? Our average word count per sentence is pretty low; our strings are mostly short (except for messages). So we may not get as much help from MT.

Maybe the average number of words per sentence would be an interesting number to take into account when we get a new project?

All of that said, these numbers would be auxiliary metrics. The word count that we use today may be looking at the end of its life. With adaptive technology and varying qualities of MT suggestions, it will become very difficult to associate all the possible variations of those suggestions to overall word count.

After all, fuzzy matches are based on translation memories, on a predetermined percentage of similarity to an entire segment previously translated. How would we use such a strict concept for all the different parameters when working with MT and adaptive technology?

Today, most of the time, the combination of MT and fuzzy matches constitute a system that outputs some mixture of “fuzzy grid for 75 / 85% and above” and “discounts for MT suggestions below that threshold.” End-clients and agencies calculate edit distance to get an informed view of whether the MT is still helping us (or if it is helping too much). And that is the system: “fuzzy with some MT discount.” Edit distance is also great to detect patterns that will improve MT output: if we’re making lots of changes, the MT may need some improvement.

But with adaptive technology and who knows what other forms of AI-powered augmented translation, how are we going to fit the fuzzy grid into this? We won’t. Translators will be paid based on time spent working. So everybody will change how they work and everybody will win. Dear translators, start thinking how much your hour is worth. It is about time.

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