“It is tough making predictions: especially about the future.” Yogi Berra
In March 2018 www.Slator.com published a comprehensive white paper titled: “Slator 2018 Neural Machine Translation Report”. It is a timely report that sets out to examine the current status of the translation technology, Neural Machine Translation. The report weighs up the pros and cons of the technology, looks at the growing embracement of it by big and not so big players, and looks to answer the question as to whether NMT is here for the long-term, an if so, what paradigm shifts will it cause.
Ray Kurwell, a serial inventor, says in his fascinating and thought-provoking book: “The Singularity is Near” that: “Inventing is a lot like surfing: you have to anticipate and catch the wave at just the right moment.” Of course, Kurwell was not the first to point this out. He was predated by a writer called William Shakespeare who advised that: “There is a tide in the affairs of man when taken at the flood, leads on to fortune.” The Slator report sets out to examine whether there is a tidal flood with NMT that others should now be looking to ride to their fortune.
The 37 page report, which can be purchased at www.slator.com, boldly declares upfront in its Executive Summary that NMT has become the “new standard in machine translation”. It bolsters this assertion by pointing out that in the last 12 months the number of NMT providers has quadrupled from a base of 5 to 20. Though perhaps more pertinent than the numbers is the quality of the companies adopting the technology as their go-to language solution. More importantly, NMT is being seen as a solution by major entities in both the private and public sectors. All of this painting a rosy picture of health for NMT’s future.
The report does accept that as of March 2018, NMT was still a niche movement. But the report goes on to caution that this narrow status might be a fleeting one, with exponential growth being driven at an increasing pace by the energy and finances of the Big Tech companies and the monolithic public services entities now involved. Added to this financial potency is the fact that the technology required to run NMT is decreasing in cost. In addition, the availability of giant, clean data corpora is growing.
Many of the Big Tech behemoths such as Amazon, Google. Microsoft, IBM and SAP, to name just a few, have committed themselves to making NMT work as a solution for them. The market for these companies is global. In order to drill down in to the locales of this global opportunity they realise they need an affordable solution for the language challenges involved. It seems they have decided that NMT is their champion.
Yet, as the report points out, NMT only became a viable player a mere four years ago. And incredibly, in those four years NMT condensed the equivalence of 15 years of statistical research in to this short period of time. Google, for example, say they replaced a system that had taken them 12 years to develop by an NMT system that took them a mere 18 months to create – a staggering 1.5 percent of the time.
The report highlights a few 2017 milestones:
- There has been a number of key release announcements by Big Tech players such as Amazon, and by what the report calls “boutique” providers, such as KantanMT.
- The deployment of NMT in both public and private sectors as a solution. (The European Patents Office (EPO) told Slator of their satisfaction with the ability of NMT to translate huge volumes of text).
- NMT has proven to be effective in translating stringently controlled material such as required by the EPO, and is also proving suitable for translating massive amounts of text in a real-time environment, as with Booking.com.
As is the way of developing business ideas, the pricing model has not yet been standardised. For Big Tech companies, the provision of translated texts is a service they are willing to provide their market in order to gain market share. The report says of boutique suppliers that they tend to charge “bespoke and flexible” pricing, depending on the service required. As of yet, there is no stock pricing matrix. Although the report predicts that with all the “various ways technology is changing how translators work, the industry is likely to switch its pay model from a per word to a per hour [charge].” Tony O’Dowd, CEO of KantanMT warns the language industry that the traditional approach to translation is: “… dead (or in its twilight zone)”.
However, NMT is not being trumpeted as the panacea for all ills. For many, there are still a lot of known unknowns to be tackled. For example, there is a lively debate ongoing in the industry as to what sort of data is necessary to create a fluent NMT engine? Some argue that this is like the proverbial “how long is a piece of string” conundrum; with factors such as language pairs, subject matter, quality of data, the algorithm involved, and so on. However, Tony O’Dowd is a lot more sanguine in his approach to the debate: “…it’s all about the quality”, he asserts. Tony believes that it is highly cleansed and aligned data, and not huge volumes of data, that is the secret to producing quality NMT results.
And of course, as with all empirical matters, it is not surprising that another vigorous debate surrounds the topic as to what constitutes quality. The report examines this debate as to how exactly quality can be, and should be, assessed. The report gives the views of different players on this tricky subject. The debate looks at technical quality testing, such as the BLEU score, and asks whether the ultimate assessment of quality can only be done by a human? Underlying this debate is another one within the industry as to whether quality is and should be a gold standard; a never to be tarnished status; or whether quality is what the customers deems quality to be? For example, does an online retailer, using real-time translations to communicate, need the scientific precision of a life science company selling life-critical equipment?
The report also brings good cheer in predicting that there will be a whole industry of sub-markets required to service the behemoths with high quality corpora. This, the reports says, is already a multi-million dollar business, and is set to grow. For some global companies it makes more sense for them to buy in ready-made corpora, than trying to create them from scratch. It is also true that many of these global companies would see the “boutiques” as a way to go for their NMT services rather than trying to build it themselves. A good example of this outsourcing model is the recent creation of the iADAATPA Consortium, an EU initiative that is tasked with developing the next generation Machine Translation platform for European Public Administrations.
Finally, as to the future of NMT? According to Kirti Vashee of SDL: “Those who best understand the overall translation production process and deploy NMT … will likely be the new leaders [of the language service industry].”
Don’t say you haven’t been warned!
Aidan Collins is a language industry veteran. He works in the marketing department at KantanMT.