Among the list of technologies that have radically changed our economy in the last year is a handful that did not receive the same level of attention as artificial intelligence or self-driving cars. One, in particular, is called Neural Machine Translation (NMT), a major breakthrough in language technology that some believe is a turning point in how business gets done.
The Internet and the connectivity it facilitates is primarily responsible for what we now call the global economy. Emails, web pages, and mobile applications have created a marketplace for ideas and products, as well as empowered organizations to collaborate instantly from thousands of miles away. But for as small as the world is today, it can get smaller, and language is a major part of that.
What is Neural Machine Translation Used For?
NMT, a deep learning technology, appears to have achieved a breakthrough in fluency that will have far ranging impacts throughout the business world. “Linguistic technology that works at fluent or near-fluent levels would be enormously impactful for business of all sizes,” says Denish Gachot, CEO of Systran Group, a leading company in the language tech industry. “Language barriers are still regularly identified as one of the primary obstacles to getting deals done, to reaching new markets, and impeding the efficiency of business operations.”
If you are not already familiar with NMT, here are three things you need to know.
It Is Powerful
The last few years have seen huge leaps in machine translation abilities. Most anyone who has used the Internet has interfaced with a translation tool at some point – be it on Facebook or the Google translation feature – and likely experienced extreme disappointment. What makes NMT different from its predecessors is its soft-alignment, or its ability to translate entire sentences based on context and language patterns, rather than just going word by word.
Systran’s version of NMT, known as Pure Neural Machine Translation (PNMT), was one of the first to reach the market. It is currently capable of translating between more than 100 different languages. And because of the almost human intuition of soft-alignment processing, this open-network frame allows the system to provide more reliable, accurate translations than have ever been available before.
Small businesses can benefit from this technology in a number of ways. Addressing client concerns, marketing to a new area, or answering questions from foreign investors? Any written communication, particularly of a technical nature, can be translated by NMT quickly, accurately, and into multiple target languages.
It Is Improving
Machine learning technology is not new, but it is finding new ways to make an impact. When we hear about machine learning, we think applications like facial recognition or self-driving cars. In a surprisingly short period of time, these programs have learned how to distinguish minute human facial features and navigate traffic with minimal human training. Instead of painstakingly programming every piece of information, the machine is taught how to learn and then set loose on a quest to become an expert.
“Neural Machine Translation…considers the entire input sentence as a unit—like you would comprehend a whole image rather than its individual pixels—taking into account the nuances of speech and meaning,” writes Stephanie Mlot for PC Magazine.
Translations are not made one word or phrase at a time. NMT can look at the body of work being translated as a whole. Interestingly, this is not done by comparing the text to a large data set of other translations, but rather is “understood” in a neural sense. The developers of this technology are not even entirely certain what mathematical calculations are being made inside the “mind” of the translation machine.
Pair that neural capacity with its deep learning function and the technology can become highly adept at industry-specific translation requirements, no matter how technical. That can help small businesses that would like to work internationally but cannot afford a team of translators.
It Is Accessible
All of this is important for small businesses because it is available technology. Emerging technology trends like this are not meant to be kept in the hands of large corporations. They are intended to trickle down, improving all the way, until they are wielded by none other than the every-day companies that make the world go round.
“The applications for this technology are not limited to the governments, law firms and international corporations that already operate all over the globe,” says Gachot. “Small businesses can just as easily leverage NMT for any number of applications. It will even become available to small freelancers who use online marketplaces to share their goods and services as those markets integrate the technology into their platforms.”
Translating documents and business communication, even simple ones like advertisements or product descriptions is a costly process that requires time and manpower, which is why many companies are limited in what they can do internationally. NMT changes that.
For small businesses, the world just got a little smaller.
Brain Photo via Shutterstock
This article feels like a paid endorsement of Systran Group, which is fine if that’s what it is. But as a longstanding translator and translation project manager, I can definitely tell you that if a company attempts, as this article implies, to translate their marketing materials, contracts, legal documents, even simple correspondences, etc. using machine translation, then it has another thing coming to it. These technologies at most can be used to do a cursory check of already-translated materials, and even then it many times misses the mark.
There’s also the question of non-Roman scripts. I’d like a company to attempt this little experiment: translate some marketing materials, perhaps just 1 page, about 200 words, into Arabic using machine translation. Then give it to a native Arabic speaker and get their critique of it. Good luck!
Also, there’s the question of targeting. For example, not all Spanish is the same. In fact, each country has its own types of Spanish (and sometimes even in the same country there are different types). Machine translation does not understand this. So say you’re translating marketing materials, which many times uses buzzwords, slang, etc. for the Mexican market but use a machine translation that uses words and terms more suited for Spain, then your translation is a failure.
I agree with Henry. The author of this article should have done more research. MT certainly has its place and is getting better all the time. But when one sees glowing reviews of the programs, one should dig a little deeper. slator.com is an excellent resource.
Marketing documents are a particular bad idea. They should be translated or rather transcreated by someone embedded in the target culture and with a deep understanding of both the industry specifically and marketing in general.
I was once a translator but now own and operate a translation company. Language is not easy!
I agree with aspects of both of the above commenters, but only in part. Sure, machine translation is hard when you get into slang and dialects of languages, but to disregard what NMT has achieved is a bit odd.
Companies like mine that need to translate massive volumes of technical material have had great success using NMT. We partner the software with a translator, which has reduced our time spent translating materials exponentially. Our specific application won’t be everyone’s, but we do need fewer translators than before…so I would understand why there would be resistance to this innovation.
I don’t use Systran, so can’t comment on their tech, but all the heavyweights are getting in on NMT. Time to get on board or miss the train!