With the recent explosion in popularity of the Amazon Echo and Google Assistant, the idea of technology you can actually communicate with on your own terms has suddenly become a reality. The once futuristic, Sci-Fi-like concept is now a reality.
There are plenty of things to get excited about that these machines can do. But for those of us working in language translation services, there’s a lesser known feature of this new type of emerging technology that we should pay attention to: its impact on language and machine translation.
Alexa (the AI behind the Amazon Echo) currently speaks three languages and Google Assistant speaks nine. Neither of these are record-breaking figures. But the technical evolution that has enabled the AI to communicate in just these languages is quite remarkable.
If we continue at this pace, we look to be on the verge of a revolution in the world of global communication.
For businesses looking to expand their own marketing to an international audience, it’s time to get up to speed and make sure your company is part of this future world of increasingly seamless multilingual communication.
Machine translation: Problems and solutions
Languages are a whole lot more complicated than most people give them credit for. And historically, machines haven’t been great at interpreting context and nuance.
Machine translators can fairly easily work out that dog, Hund or chien all refer to the same thing. The problem comes when words and phrases start to mean different things based on context.
Take, for instance, the following two sentences:
“The man feeds the dog”.
“The man eats the dog.”
The basic components of this sentence are almost identical. The subjects and objects are exactly the same, and the verbs are ostensibly synonyms. Grammatically, you’d expect them to mean the exact same thing, but obviously, they mean something completely different.
Any old human can understand this based on our knowledge of men, dogs and feeding, but computers are going to have a little more trouble. We found a similar translation fail example some time ago when a translator failed to understand the difference between serving food to a vegetarian and serving the vegetarian as food.
The nuance involved with negotiating these different semantics is too complicated for us to teach computers. So, essentially, the computers have to learn it for themselves. That’s where machine learning and AI comes in. The technology essentially feeds enormous amounts of language and translations into an algorithm, from which the machine learns to deduce context by comparing it to other similar examples.
In this sense, it’s very similar to how children learn a language as they grow up: by simply hearing it enough times that they work the meaning out. And it’s precisely with this technology that machine translation has been quietly improving over the last few years.
In fact, Alexa herself comes with a specialised feature called Cleo that allows you to feed source material into the into the algorithm and ‘teach’ her your language.
What does this mean for the future of global business?
It might come as something of a shock to hear, but we’re not actually all that worried about machines suddenly taking all of the translation projects. In reality, we’re working in different areas. Nobody seriously expects machine translation and Alexa to become good enough at translation to translate detailed technical documents and marketing materials into other languages – at least not imminently.
But what we can expect – and indeed are already seeing – is a change on the human side of business. The real potential of the technology is in helping people from across the world to interact and communicate with each other. Machine translation shows increasing promise, not strictly as a medium for marketing, but as a medium for communication and ‘door opening’.
In this brave new world of ‘global Britain’, savvy business leaders everywhere should pay careful attention to developments that allow them to build networks and make new connections around the world. If an AI system on our phones means a UK product development team can speak directly with a manufacturing team in China, all of a sudden business can take place much faster than it would need to if everything had to be routed through an interpreter – which is a job that is potentially more affected than written translation services.
The prevalence of AI like Alexa is driving improvements in machine translation and accelerating a wider movement that seeks to break down barriers and bring the world closer together.
It’s an industry we’re proud to be a part of. As the world changes, businesses will have to become better at finding customers and business partners in new markets. Our language translation services can help with that.
