First of all, I’d like to wish you an excellent 2020! May it be full of projects, full of texts and full of new challenges! Speaking of challenges, rather than looking back over the past few years, this is a good time to look to the future and draw up a list of the major trends that await us in the language industry in 2020!
The idea of transcreation is not new. It has become increasingly prevalent in recent years, and 2020 is set to reinforce this trend. But what exactly is transcreation?
Often presented as the Rolls-Royce of translation, transcreation is not just a marketing idea sold by agencies. It responds to the growing need not only to translate, but also to adapt content to the target audience and culture. The idea is to retain the same message and its impact on the audience, but not necessarily by expressing it in the same way. We are therefore at a crossroads between pure copywriting and translation. To put it simply: transcreation is writing new copy directly in the target language, but based on the ideas and information in the source text.
Communication trends in general, and in all fields, show that we are moving more and more towards personalised content. This means that linguistic and cultural differences need to be erased and/or replaced in order to maintain the same impact on each target market. This is precisely what transcreation is all about.
But successful transcreation is a real challenge. You need a complete command of both the source and target cultures, otherwise how can you understand the allusions and references in the original text and how can you render them with the same impact for the target audience? Are you entering a new market? Do not hesitate to contact me, I will be able to provide you with the appropriate solutions.
Translation and media localisation
It’s no surprise to anyone. The media are taking on ever more diverse forms, and the need for translations is booming. The multiplication of streaming offers, the preponderance of visual formats, whether in the form of videos or images, on social networks and the ever-exponential increase in content are a driving force for the language industry. Subtitling and dubbing have become real markets for linguists. New dedicated players are even appearing, bringing real expertise to the table.
However, media translation is full of new challenges. Particularly when it comes to content intended for online publication. The immediacy of these channels demands ever greater responsiveness from the players involved. It also requires ever more advanced technical knowledge to respond to the platforms and SEO imperatives for indexing content.
Machine translation: Neural networks and deep learning
Machine translation is nothing new. But where it used to remain marginal and often disparaged in professional circles, it is now a ubiquitous feature. Since 2015 and the emergence of neural networks, machine translation has made a real leap forward. It may not always be perfect, but its contribution is undeniable.
Google translate needs no introduction – everyone uses it in one way or another. While there are still many problems and the translations are far from perfect, it is a very good example of the evolution of these solutions. Whether it’s Google’s engine or another, these technologies are now finding their way into professional translation processes. Whether by integrating these engines directly into workflows (post-editing, augmented translation, etc.) or simply as support, they are becoming indispensable.
But where the various engines have been battling it out for the past few years over the best technologies, 2020 is likely to bring its share of changes. While the algorithms are still the determining factor, it is above all the resources used to drive these engines that are now the focus of attention. General-purpose engines are showing their limits, and variations based on resources from specific fields, or even entire companies, are appearing. New roles are emerging for linguists:
- preparing resources for training systems;
- engine maintenance and improvement;
- quality assessment;
- post-editing, etc.
I’m sure I’ll have the opportunity to talk more about this in other posts…
Post-edition & Enhanced translation
Project management is one of the aspects that language service providers are always emphasising, and one that underpins the ISO standards governing our industry. However, it is also one of the aspects that is least often talked about and never seems to change. Indeed, processes have tended to become standardised between the various players. And yet there are changes here too!
With the emergence of machine translation systems, the machine has taken its rightful place in the translation process. The standard process:
Translator > Reviewer > Quality control
is no longer the only one used by agencies looking for cost savings and greater productivity. Post-editing now has a large share of the market and is imposing its own workflows:
Machine translation > Post-editing > Quality control
This is nothing new! These processes have been commonplace for several years. But a turning point has come and is still coming. This new process has often been imposed on translators. Sometimes in a clumsy way, or even completely dishonestly. Some pass off post-editing as simple proof-reading, causing many linguists to reject these solutions. The big change is that the “good” agencies (let’s face it, there will always be cheats) are no longer hiding and are openly offering this type of work. Better still: full training and accreditation for these tasks is now available. Indeed, working behind a machine does not require the same talents as working behind another human. Some flaws can be spotted straight away when we are prepared.
Machine translation still strikes fear in the hearts of linguists and clients alike. We’ve all heard or even uttered the phrase “it’s Google translate”. This phrase invariably indicates that the expected quality was not present, sometimes wrongly, but that’s another debate…
Halfway between post-editing and ‘classic’ translation, new processes are emerging. These give greater latitude to translators and offer productivity gains for companies. Various workflows are emerging to reconcile machines and linguists to the benefit of both parties.
Augmented translation is one example. Not quite post-editing, nor quite traditional translation, this process makes the most of machine translation without imposing it. The aim is to maintain optimum quality and fair remuneration.
Like pure machine translation or post-editing, the relevance of this process depends very much on the source texts, the languages considered, the domains concerned and the engines used. Nevertheless, they can be a win-win situation for everyone, gently shaking up linguists’ habits.
Enhanced translation processes are among the elements that I explain at greater length and put into context in my consultancy services.
New site, new life
If you’re reading this, you’ll already know that 2020 marks a new turning point in my career. After 7 years working for various companies, I’ve decided to go freelance again.
So here’s a new website and blog. Not to mention a new me, ready to take on the world and, above all, to support you in your projects!
May 2020 be a profitable year for us all!