Why Does Machine Translation Matter?

Why Does Machine Translation Matter?


Never before has there been so much information available to users. We have reached a point where the volumes of data created every day are simply unprecedented. The only problem is that not all of this information is accessible in all the languages spoken by users around the world, which creates communication barriers.

New era of data volumes

User-generated content (USG) – vlogs, Facebook and Twitter posts, online reviews – is the fastest-growing type of content. It has greatly contributed to the fact that the volumes of data produced daily are currently exploding to the point that more data has been created in the past two years than in the entire previous history of the human race.

That sort of explosion presents companies with new types of challenges that they never had to face before. They now need to assimilate and analyze those vast amounts of information to determine if it is useful or relevant to their customers.

Businesses which don’t successfully embrace these challenges risk quickly becoming irrelevant. We have seen that happen before, particularly in the retail area. One of the recent examples is an international toys and baby product retailer, Toys R Us, which failed to successfully identify their customers’ preferences and keep up with them.

Time is key

To add to the pressure, some of this content is also time-sensitive, meaning that its lifespan can be very short.

Data charts on a piece of paper

Businesses need to make sure that they are able to analyze information quickly, before it goes out of date.

For instance, cyber security companies need to constantly update their knowledge about possible security threats as those can evolve in a matter of hours. For those type of businesses being able to disseminate information, updates, and policies among the employees in a form that is fully understandable, which is likely to involve localizing information, might mean the difference between being successful and being irrelevant.

Looking from another perspective, content that companies produce as their sellable product is also at risk of quickly becoming out of date. When we think about news agencies, the type of content they work with can only keep audiences engaged for a limited periods of time. For example, nobody wants to read a football match report a month after the match has taken place. The readers want to have access to that report within minutes from when the game finishes.

The role of machine translation

How do we then embrace the explosion of the volumes of content being produced everyday and its time-sensitiveness? How do we make sure it is still usable and available to wide audiences speaking different languages?

Translation is all about making information widely available and spreading the knowledge. In the words of Translators Without Borders “information in the wrong language is useless.” However, it turns out that traditional ways of translating have long become insufficient to handle the amounts of data companies deal with every day.

Traditional translation services simply no longer scale to the needs of modern enterprises without leveraging technology in an agile and substantial way.

That is why machine translation has been gaining so much interest as a means to alleviate the barriers resulting from urgency and large volumes. Thanks to machine translation, content that would previously never get translated due to prohibitive costs and deadlines, can now be localized and made available to wider audiences speaking different languages, therefore increasing the knowledge economy.

Tech companies such as Amazon, Microsoft and Google have been quick to grasp this opportunity and keep competing vigorously with each other to excel in the machine translation domain. Amazon Translate has launched its services in 113 new language pairs at the end of October as another step towards challenging Google Translate’s domination in the realm of public MT.

What’s in it for linguists?

It is all too easy to get excited about any new technology. What we should really be focusing on is how that technology impacts humans and how it helps them achieve what needs to be achieved.

For corporate businesses, using machine translation means being able to stay on top of all the information that needs to be digested and disseminated, which in turn plays a key role in allowing those businesses to remain relevant on the market.

For linguists, the presence of machine translation means that their role is inevitably changing. Just like corporate businesses need to adapt to new market conditions, linguists also need to embrace new circumstances and adjust their skills accordingly.

As more content gets machine translated, the more machine translation post-editing opportunities there will be for skilled post-editors.

Those linguists who successfully embrace machine translation post-editing, the technology powering machine translation and learn how to use those as aids in their everyday work will not only thrive in the new language service landscape, but will also see a surge in the number of clients that will want to work with them.

Written by Kasia Kosmaczewska
Kasia Kosmaczewska
Kasia Kosmaczewska is Machine Translation Programme Manager at TranslateMedia. She has extensive linguistic experience and a keen interest in machine learning. She spends her free time reading about socio-politics, practicing pilates and travelling.

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