Following our launch of KantanNeural™ engines as part of our KantanFleet™ repository of pre-built MT engines, we received a number of questions and interest around the product. To address these questions, we asked Tony O’Dowd, CEO and Chief Architect of KantanMT.com a few questions about the Neural Machine Translation engines on KantanMT, the features and benefits of these engines and the impetus behind launching KantanNeural. Continue reading
Giulia Mattoni, an Italian Translation Technology student from DCU talks about her experience using Machine Translation for evaluating player support content localization. Giulia’s fascinating view illustrates why this area needs further research, and how she used KantanMT to evaluate MT and post-editing for this type content. Continue reading
You have your finger on the pulse of latest technologies, and you are proud to use the latest automated technology for your localization needs. But, sometimes it might feel like you are still stuck in the 90s when it comes to reviewing your Machine Translation (MT) output for quality – especially, if you are using spreadsheets to collate your reviewers’ feedback on segments.
Traditionally language quality review for MT involves the Project Managers (PMs) sending copies of a static spreadsheet to a team of translators. This spreadsheet contains lines of source and target segments, with additional columns where the reviewers score the translated segments according to a set of predefined parameters.
Once the spreadsheets are sent off to the reviewers, PMs are completely in the dark – with no idea how the reviewers are progressing, when they might complete the review, or if they have even started the project.
If that sounds tiring, imagine what the PM has to go through!
Elodie Vermant, a Swansea University student, studying for an MA in Professional Translation, shares her experience on using Machine Translation for the first time at Swansea University.
The MLTM11 Translation Technologies Module is taught by Dr. Maria Fernandez-Parra, Lecturer, Languages, Translation and Communication at Swansea University. Read more experiences from her students.
The translation industry has experienced a great shift in the past number of years, and not many can say they haven’t been affected. The movement to automate translation processes, driven by a remarkable increase in the demand for accessible multilingual content and price pressures on localization professionals can be seen at every level of the translation industry.
TAUS (Translation Automation User Society), a translation industry ‘think tank’ was founded in 2004 as a result of a roundtable held at the Localization World Conference in Seattle at which a group of some of the biggest IT companies in the world; including Oracle, IBM and CISCO sat to discuss the topic of automation and explore ideas of how to support the movement and those it affected by it.
Jaap van der Meer, Founder and CEO of TAUS talked to KantanMT about the evolution of one of the industry’s most well-known resource centres and the rapidly increasing developments in translation technology. He also shares his opinions and thoughts about the translation profession which he sees as having no escape from this global move to automation.
For Jaap, TAUS began as an ideology; he wanted to “help the world communicate better and create bigger opportunities for the translation sector”. He notes how the translation sector differs from other industries in that most industries have developed shared approaches, best practices and common metrics to support themselves and others working within these industries.” The lack of this he says is something that has created a “huge barrier to efficiency and innovation” in the translation industry, and when we remove these barriers “we create a much bigger opportunity for each individual player in the industry”.
TAUS is synonymous with automated translation, and in particular with machine translation. Yet, while Jaap would suggest that this is only one piece of the puzzle, he does believe that in time “every company that operates internationally will have to start using it.”
Machine translation has experienced incredible growth in recent years, both in terms of technological innovation and wide industry adoption. Indeed, Jaap believes that “the investment that goes into improving MT technology and integrating MT and post-editing into translation workflows will be the one thing that has the biggest effect on the industry” over the next few years. He stresses however that this investment needs to feed an entire ecosystem, because MT is not stand alone. “You can’t just dump a machine translation system into an existing environment. You need to change and innovate the whole environment. There’s a lot of evaluation and metrics involved and widespread training needed.”
Another technology that he sees developing in line with machine translation is speech translation, and the convergence of both technologies. Those attending the TAUS annual conference in Vancouver in October will learn more about this as it is the conference theme. So will TAUS offer similar resources for speech translation as with text translation? Well, Jaap admits that although TAUS always tries to be “ahead of the curve”, the process of building such an extensive repository of speech corpora might be too demanding for an industry body of TAUS’ size. The solution? Jaap says they will need to “collaborate with other industry groups and also at a government level” in order to grow in this area.
So, as TAUS continues to expand its services and move into new areas Jaap’s role begins to grow and diversify. What keeps him driven on his pursuit towards language as a utility? “It’s just because I believe in it, if it were just for business, I’d probably do something else.” A nice thought knowing that that there are people working to progress an industry and ease the path for all stakeholders involved.