Data are indispensable in almost any business and industry these days. The translation and content delivery industry is no exception. Data are the key to efficiency improvements (think of machine translation and translation memory leveraging) and to quality control and process management and automation. TAUS has a unique position in the global translation industry as a neutral and independent language data network.
Recent blog posts
It takes just a day of wandering in Tokyo as a non-Japanese speaker to understand why translation innovation starts in Japan, and much less so in other places of the world. Both visitor and host are totally helpless and hopeless when trying to talk to each other. That is much less the case in Europe and North America where English often becomes the ‘langue véhicule’ for tourists and business men.
The translation industry is experiencing a most exciting time of opportunities. In my previous article - The Story of the Translation Industry in 22 - I described ten different innovation themes with an inside-outward looking perspective. In this article I take a view from the outside observing sentiments that could dampen the growth and opportunity curve of the translation industry. Political fashions seem to be leaning more towards protectionism. Companies tend to think that they are more globalized than they in fact are, and find that they are spending enough on localization. The art of localization is to exploit the differences in cultures rather than simplifying them to global standards. We knew that, but do we really practice it? Now more than ever, stakeholders in the translation industry need to be firm about their mission and the unique role they have in their companies’ and clients’ globalization strategies. They need to be “locamaniacs”.
What is a Quality Manager in a translation company doing? Checking the quality of the translations, of course. That’s what one would think immediately. But just like many other jobs, the job of the Quality Manager is changing, and just like with other jobs the reason is: data. Here are five reasons why modern Quality Managers should be obsessed about data.
On March 22-24 (2017), fifty people came together in a former clandestine church in Amsterdam to break their heads on the question how the translation industry will have changed in 2022. The story that came out can be read as an ordinary battle between man and machine, with a victory for the latter. But at a deeper layer, there is a fascinating intrigue with many threads about game-changing technologies and trends and an outcome that is perplexing even for all of us who think that they are behind the wheel today. Be careful what you wish for.
On 11 November, Daimler hosted an Automotive Translation Roundtable organized by TAUS and berns language consulting. Translation managers from eight large automotive and three large IT companies participated in the one day meeting. Goals for the day were to get the pulse of the translation sector and learn from each other. What do we have in common? Where do we differ? It comes down to this: we are not so different. And what’s more: we must work together across the translation sector to create a common ecosystem.
What makes a good conference? If you ask me, the answer is: purpose, people and program. As simple as that. Let’s start with ‘purpose’: you have to have a good reason to make people travel from all over the world to a single location and have them spend a few days of their precious time together. As Eric Liu, General Manager of Alibaba Language Services, said in his keynote at the TAUS Annual Conference in Portland last week: it all starts with a mission - “Preparing for a future that is without language barriers”. The same goes for TAUS and the TAUS Annual Conference. Why do we have a conference - what is the purpose? Because we want to work together to help the world communicate better.
Data entered the field of machine translation in the late eighties and early nineties when researchers at IBM’s Thomas J. Watson Research Center reported successes with their statistical approach to machine translation.
Until that time machine translation worked more or less the same way as human translators with grammars, dictionaries and transfer rules as the main tools. The syntactic and rule-based Machine Translation (MT) engines appealed much more to the imagination of linguistically trained translators, while the new pure data-driven MT engines with probabilistic models turned translation technology more into an alien threat for many translators. Not only because the quality of the output improved as more data were fed into the engines, but also because they could not reproduce or even conceive what really happened inside these machines.
It was Renato (Beninatto) who reminded me, in the ‘Future’ panel discussion in Dublin, that only eleven years ago (when the TAUS think tank was founded) nobody - in his right mind - would think about using machine translation (MT) technology on any job anywhere. And now? Now MT is everywhere. Insiders say that everyday computers translate 200 Billion words. That is 100 times more than the output of all human translators together. MT is everywhere and always there, except … well, except the professionals seem to have their doubts. That makes me think that the state of the industry could be better.
The question is: are we all on the same evolutionary path? Or do some of us take different turns, make shortcuts and even arrive in different places? The TAUS Executive Forum on April 25 and 26 in Beijing opened new perspectives on translation in China that many of us had perhaps not expected. China typically copies what others have already built and done before them. Fast trains are modeled to the TGV in France, electric cars are inspired by Tesla, and fashion in China follows the trends around the world closely.