3 Ways You Can Become an ‘Augmented Translator’

This is a guest post by Jonathan Grisot who works as a Senior Language Specialist in SDL’s French Language Office in Paris.

The translators working in the Language Offices at SDL are probably amongst the most tech-savvy pool of translators in the business translation industry. Their proximity to developers of a range of translation technology, ranging from TM (Translation Memory) to TMS (Translation Management Systems), to MT (Machine Translation) and other translation process-related tools gives SDL internal translators a natural advantage. The possibilities and potential for transforming business translation processes and outcomes have gone into high gear in the last four years, as a new management team began an overhaul and rationalization initiative that has already been yielding results. In the coming years, we should expect to see much new innovation coming from these strategic efforts. 

SDL is unique amongst the largest 50 LSPs in having the largest pool of in-house translators.  After the initial wave of euphoria around machine learning and "AI," the world is beginning to realize that the best results are often better accomplished by new models of (wo)man-machine collaboration than by machine alone. As tool developers and linguists begin to engage more intensively and as the dialogue shifts from FUD related factors, to true problem-solving focused collaboration, a new breed of technology and services is emerging.  

I have always felt that the best MT technology will evolve from a productive dialogue between competent translators and open-minded MT technology experts. Superior solutions emerge from process innovation entwined with relevant NLP capabilities and expertise, for the purpose of solving high-value business problems. Long-term experience in solving these problems can provide the insight needed to find optimal process-technology-expertise combinations to address the issues at hand. There are use cases where only an expert human would work and there are use cases where machines alone can handle the sheer scale, volume, and timeliness that is needed. However, in this age of digital transformation where the modern enterprise has content as the core of their digital footprint, the role of properly deployed MT can only grow. This will require a man-machine collaboration that adjusts and adapts to the varying needs and shades of grey that are needed to solve these new kinds of translation challenges.    

This post is a perspective from the translator frontline at SDL and represents an attitude that will produce superior services and technology. SDL has a broad and deep engagement with global enterprises around content management and translation challenges and it is clear that the approach needed for the future will by necessity need to be more varied. The reality before us is nicely captured by research shared in the 2019 United Nations Conference on Trade and Development Digital Economy Report, which shows that global internet protocol (IP) traffic, a proxy for data flows, grew from about 100 gigabytes (GB) per day in 1992 to more than 45,000 GB per second in 2017. By 2022, the figure is expected to stand at 150,700 GB per second.

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The future of professional translation is here. Are you ready? Translation is driving the globalization of communication, but it encompasses more than just translation: linguistic advising, review, proofreading, transcreation, subtitling, language consultancy, linguistic content management... the list goes on. No doubt 2020 and beyond is set to increase opportunities for translators to add value to their clients. But, given the rapidly changing world we now live in, how can translators evolve their own services, becoming 'Augmented Translators'?

Engage with technology

The purpose of technology in translation has always been to help translators deliver and finalize content faster. The days when translators were locked up in a library with a pile of dictionaries and a pencil to produce a translation are long gone. Today, content is processed online, from brochures and web pages to user manuals and market outlooks. Even traditional white papers are no longer exclusively published in paper format. And the list of tools, plug-ins, and technologies available to help translators to finalize and reach audiences continues to grow: translation memories, terminology databases, fragment matches, upLIFT, Neural Machine translation, Autosuggest dictionaries, and more.

Even our corporate language is changing with technology: instead of “engaging” with customers, companies “connect” with customers. Now, for those who are familiar with the technologies offered by our flagship solution, SDL Trados Studio, check out the many assumptions raised about our future by language specialists here.

Even more tech-savvy? Check the other side of the fence and see how content will impact the augmented translators’ environment. Discover SDL Content Assistant, a technology that was considered science-fiction several years ago – but is now very real.

Also, with today’s technology, the help provided to translators does not only come from the tools: now, even content creates itself. Now, it’s up to us, translators, to transform it for our local audience.

Specialize in quality levels, not only in specific industries

Fact: the amount of content to translate has reached incredible levels. While SDL translates hundreds of billions of words every year, this figure remains a drop in an ocean of all translated words. What matters is not the amount to translate. What matters is that the result displayed to your audience meets the quality level expected for such content.

However, billions of words also mean billions of possibilities, and augmented translators are aware of one truth that is the current state of affairs: there is no “standard translation”.

All translations are unique, because clients have unique needs, like their customers. And they also have unique constraints, terminologies, processes, and practices.

With the client’s needs in mind, the augmented translator will adjust their effort and the amount of time required to complete their tasks. And the productivity tools available nowadays are here to help them alleviate the burden: the augmented translator never translates from scratch.

The key factor here is to find the perfect dosage in productivity, the right balance between effort and result. It is important to have a strong understanding of the translation workflow, the tools and assets at your disposal, and your own strengths and skills. This will help assess the quality and thus reduce risks.

In fact, “quality” can only be assessed by a human mind, and this is where the augmented translator and the client can collaborate to set expectations on quality. Because both clients and translators know that a “lack of quality” also means “rework”. And while a “high-quality translation” may be expensive, a “low-quality translation” may cost even more.

Inject culture, and acquire knowledge

Augmented translators will speed up the process of integrating their clients’ requirements to get the quality needed, and that is a truth for all industries. But only if they have adequate assets to help them get started in an augmented world.

An augmented translator will take advantage of the following resources:

• Content reuse from translation memories
• Glossaries to apply preferred terminology
• Style guides to comply with formatting, grammar, and stylistic rules 
• The tone of voice or brand guides to convey the brand’s message 
• Project-specific instructions, like character limitations
• Machine and AI-enabled translation engines to accelerate productivity

All these automated tools and assets are literally “knowledge providers” to the translator, and help non-specialized translators to meet client requests even without even knowing the client. These knowledge providers are useful since all the clients have preferred terms, favorite wordings, and different rules.

Of course, this automation can also be error-prone and full of traps: terms in glossaries that do not take the context into account, incorrect source texts written by non-native speakers, corporate jargon not understandable outside of your client’s professional sphere, and more.

This is where the augmented translator has two strong cards to play: culture and understanding.

Augmented translators will be able to spot errors in the source text, avoid using offensive or restrictive content, use the appropriate language for the target audience, rewrite puns, detect dual meanings, adapt to stylistic rules, and correct erroneous terminology used by translation engines, etc.

The augmented translator walks in the footsteps of the ancient copyists and scribes and embraces the same mission and ambition: connect cultures and content to share a message.

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Jonathan Grisot started as a translator in 2007 and currently holds a position of Senior Language Specialist for SDL in Paris. He is responsible for driving Machine Translation initiatives, managing internal training and quality best practices and is still involved in various translation and transcreation projects. He is also managing the Junior Academy, a local SDL onboarding structure for newly hired SDL translators. Born in Burgundy and raised on the French Riviera, Jonathan considers his detective novels, sci-fi and fantasy books as his numerous children.