Often, when people think about translation and translators, in broad terms, they still have the image of a bookworm, thick glasses on their noses, frantically typing words… maybe even surrounded by dusty old books, in a library-type setting. Easy like Sunday morning, perhaps? What can be easier than sitting at a desk, reading a text and conveying it to another language? Even more so if a lingua franca, such as English, is involved in the process. Every jack and jackie of all trades know their way in English, nowadays, right?

Although I salute people’s dedication to self-improvement and learning foreign languages, I still feel the urge to point out that somebody who speaks or even masters a certain foreign language is not necessarily a good translator, because they lack translation technique skills, which are acquired in time, with lots of study and practice.

And I would like to draw your attention to a very specific kind of translation, namely on the importance of translation in humanitarian response. Unfortunately, when a crisis occurs, be it a virus spreading worldwide at a very fast pace, a  war zone, wildfires, hurricanes, earthquakes, volcano eruptions – you name it – consequences usually tend to have a global impact. Hence, communication is essential – between parties who don’t necessarily speak the same language – first responders, doctors, researchers, officials, affected people etc.

Basically, the translation & localization industry has the power to help both humanitarian volunteers and affected people without being actually present in the field. That’s some magic, isn’t it? Keep in mind, according to Translators Without Borders, more often than not, the people in need of help don’t have the literacy skills to read, understand and react to complex texts, what they need is plain language, in their mother tongue. Thus, the need for international guidelines such as the CHS – Core Humanitarian Standard Commitments emerged, based on the idea that plain language makes text easier to understand, to put into practice and easier to recall at a later date – basically, everyone appreciates plain language, don’t they?

Some examples of suggestions for plain language put forward by TWB are the use of personal pronouns such as “you” and “we” for engaging readers and making it clear who is responsible for certain actions, rewriting sentences so that they contain fewer than 20 words, given that shorter sentences are easier to comprehend and paraphrasing or replacing technical terminology with alternatives that are familiar to all readers.

Now, coming back to the need for language solutions in humanitarian work, in 2018, TWB estimated that more than 3,000 languages were spoken by the millions of people affected by humanitarian crisis, with many of them not speaking the languages of humanitarian aid workers. Usually, we are talking about the  most vulnerable people worldwide, sometimes with lower levels of education and little or no access to technology. No need to delve into the idea that language provides access to information, information is power and so on…

I’m sure everyone can see the high stakes and great challenges of overcoming language barriers when it comes to humanitarian actions. Professionals in the language and localization industry do get involved and help out as much as possible, and sometimes they do this just for the reward of having enhanced much-needed communication and having contributed to the greater good.

However, I believe we are talking about team work here. Disasters should bring people together, regardless of the language they speak. Improvements have been made, but there is still room for collaboration and development, especially in the field of adapting technology  to such communication needs. In recent years, we have witnessed major developments of machine translation, CAT tools, voice recognition and artificial intelligence. Nevertheless, such developments are usually oriented towards marketable and profitable languages; minority languages, e.g. Swahili, Bengali, Rohingya, tend to be left behind.

TWB suggests that one way to support future machine translation and to lower the gap between languages could be creating a huge database for under-served languages, including voice, original text and translated text data. Another challenge, you might say. Maybe. But how can one know, until they actually try?

If you want to contribute, either on a professional or a personal level, you are welcome to do so. If you are either a language service provider or a tech-focused enterprise, you may share parallel data, volunteer,  support TWB’s initiative “Gamayun” or get involved in fundraising. So, when is the last time you felt that you actually made a change for the better?

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