The Secrets of Translating like a Well-Oiled Machine

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The Rosetta stone paradigm translations. Hans Hillewaert Wikimedia (CC)

This article is written by José Pichel Andrés and was originally published in Spanish in the online journal, El Español. It has been translated into English by Carlos Collantes from the Professional Services team at KantanMT. The article has been edited slightly for readability, but we have made all attempts possible to retain the original flavour of José’s article.

Read the article in Spanish here.

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Researchers today are redefining Machine Translation. Though it is still a far cry from being completely satisfactory, it displays a rapid development, thanks to new systems like Neural Networks. Continue reading

Why Neural Machine Translation (NMT) Might be the Next Big Step for the Industry

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Last month, Dr Dimitar Shterionov published an article on MultiLingual, a highly respected magazine on the localization industry, where he talks about the changing landscape of Machine Translation (MT) in the language industry, and how Neural Machine Translation (NMT) has very recently emerged as a revolutionary new paradigm in MT research.

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Let us take a look at some of the key points put forward by Dimitar and what is happening with NMT. Thanks to increasingly robust technological advancements, Machine Translated content has proven to be incredibly accurate, especially when compared to the output of traditional MT models.

What is Artificial Neural Network (ANN) and Neural Machine Translation (NMT)? Continue reading

What’s New in eCommerce in 2016? More Localization and Better Machine Translation

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If the post-Black Friday sales numbers are anything to go by, there’s no question any more that the face of eCommerce is changing, and with it, the brick-and-mortar retailers have started rethinking their business strategy. As this news piece about Scotland experiencing a major dip in shoppers goes on to prove, demand for online shopping will increase substantially in 2016. This in turn means that the need for content localization and translation for eTailers (online retailers) will be even more pressing during the coming new year. As the often quoted Common Sense Advisory report points out, 72.4% of consumers are more likely to buy from a site, which is in their native language.  Indeed, localization is no longer a good-to-have feature – it is now a must-have for all eCommerce businesses that aim to sell their products globally.

Chris Bishop, Managing Director of Microsoft Research, Cambridge, UK points out that “by 2026 we will have ubiquitous, human-quality translation among all European languages, thereby eliminating the language barrier throughout Europe.” Bishop’s prediction does not sound far off the mark at all when we take into account the fact that in the past ten years, Machine Translation (MT) has improved by leaps and bounds. Early MT was rules-based (RBMT) and required sets of linguistic rules, and it worked moderately well within a prescribed domain. However, this was resource intensive and cost prohibitive for many.

By 2026 we will have ubiquitous, human-quality translation among all European languages, thereby eliminating the language barrier throughout Europe

Chris Bishop, Managing Director of Microsoft Research, Cambridge, UK

The turning point for using MT in business came with the advent of the Internet, the SaaS model and the open source development model for software. These new changes in technology helped build the foundation for Statistical Machine Translation (SMT) research, and subsequently the open source development of the Moses Decoder. Moses enabled researchers and private companies to commercialise Statistical MT and develop it to the custom solutions it is today. The year of 2016 and beyond, will see further research in the fields of Natural Language Processing (NPL), Deep learning and machine learning, contributing directly to immense improvements in the fields of Custom MT.

The KantanMT Business Team published a new white paper, which provides an in depth understanding of how eTailers in 2016 will be affected by Machine Translation, and also goes on to discuss how Custom Machine Translation when compared to generic MT systems, will emerge as the clear winner in solving eTailing localization issues in the coming year.

Here are some of the highlights how MT will evolve in 2016 for eTailers:

  • eTailers will use a combination of only CMT or CMT and Human Post-Editing to reach new markets ahead of their competitors
  • With increased multilingual customer demand for products, content translation will find support in auto scaling
  • Custom Machine Translation will be used more widely as eCommerce customers expand globally

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Summary:

Machine Translation is no longer a luxury. It is an essential component as a Tier 1 application to support global business. The purpose of this paper is to highlight how Machine Translation and more importantly Custom Machine Translation technology has come of age, in terms of quality, speed and scalability. During 2016 and beyond eTailers need to ensure that they review their globalization strategies to reflect these advances in technology, so they can maximise their global growth potential.

Download the KananMT white paper on eCommerce today!

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