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Welcome to our blog section where we have collated a range of blogs from different authors on themes related to machine translation, translation technology and application thereof.

If you are in the localization industry and are interested in understanding how you can benefit from machine translation while getting your staff ready, read the blog “Achieving an ROI from Machine Translation while Keeping Translators ‘Happy'” where our author discussed how LSP’s can achieve significant return on investment (ROI) from machine translation and at the same time keeping their staff happy. It addresses the problems which many LSP’s who are planning on applying machine translation as a strategic support tool are facing and discusses the importance of having a data and machine translation strategy for best in class MT output and ROI.

In the blog “No Data – No Problem” we discuss one of the most common  problems LSP’s are facing when starting to apply machine translation, which is what to do if there aren’t sufficient data or linguistic assets available to build a new custom machine translation engine.

One of our popular blogs discusses “The State of Neural Machine Translation (NMT)” which is about the exciting and promising new approach to machine translation. Here Prof. Dr. Philipp Koehn gives a Technology Overview about neural machine translation and talks about its technical limitations with its advantages and disadvantages as well as its current deployment.

Our blog about Deep Neural Machine Translation (Deep NMT) discusses the evolution of Neural Machine Translation (NMT) and provides answers to common questions such as what the real factors are that affect the quality of the machine translation output and how to cater for that in your projects.

Finally, our latest blog “When, Why and How to Migrate from Statistical to Neural Machine Translation” takes a look at upgrading Statistical Machine Translation engines or even replacing them with Neural Machine Translation or Deep Neural Machine Translation ones.

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    When, Why and How to Migrate from Statistical to Neural Machine Translation by Dion Wiggins

    It has long been established that a customized for-purpose machine translation engine will deliver higher quality translation output with a relatively small amount of training data compared to a generic MT engine such as Google. But with the advances brought about by Neural Machine Translation (NMT) and Deep NMT engines, the results even from generic engines are notably better than the preceding SMT technologies. But what about customized MT engines? Are they still good enough to beat Google and other generic engines? Should SMT engines be upgraded or replaced by NMT/Deep NMT engines altogether? In my earlier blog post “Riding…

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    Riding the Machine Translation Hype Cycle – From SMT to NMT to Deep NMT by Dion Wiggins

    There is a running joke in the translation industry that machine translation will be a solved problem in 5 years. This has been updated every 5 years since the 1950’s. The promise was always there, but the technology of the day simply could not deliver. However, there has undoubtedly been progress. When we started our company over 10 years ago, MT was considered a joke and ridiculed. At the time, we looked to purchase MT technology, but were unable to find any technology that could rise to the challenges that we needed to address. At the time we had the…

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    The State of Neural Machine Translation (NMT) by Philipp Koehn

    Neural Machine Translation (NMT) is an exciting and promising new approach to Machine Translation. However, while the technology is promising we still have some way to go to commercial implementations that can rival Rule Based Machine Translation (RBMT) and Statistical Machine Translation (SMT) in all use cases. Some recent claims by industry players to suggest that near human quality is right around the corner for all of us, might be a bit of an over-simplification. With this brief blog, I would like to provide a view of the current state of affairs. Technology Overview First of all, neural machine translation…

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    No Data – No Problem!

    Want to build a fabulous new custom machine translation engine for a new client of yours? There is, however, one problem: You just do not have enough data you can give Omniscien Technology to build this engine with? What do you do? Is there a solution? Fear not – there is a solution! At Omniscien Technologies we often encounter customers who have little or even no data at all and so we have developed a set of processes to address such cases. Usually this scenario happens when there is a client who is new to the LSP and no historical linguistic assets are available or it also happens…

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    Achieving an ROI from Machine Translation while Keeping Translators “Happy”

    It would seem a paradox that LSP’s can achieve significant ROI from Machine Translation (MT) and keep localisation staff happy. While seeking efficiencies in business right from the early days of the industrial revolution has always resulted in shifts of where human efforts are applied and these changes don’t come easy, most staff members presented with machine translation output for post-editing are frustrated mainly at the poor output they are presented with. Poor output can even go as far as for example wrong domain specific output which will likely force an editor to rewrite significant sections of a document and…