New Feature Release: Interview with Marek Mazur, Development Manager, on features and benefits of KantanTranslate™


Last week we announced the launch of KantanTranslate, a new feature on our KantanMT platform, which will make translating small fragments of content simpler and faster. We interviewed the man-behind-the-scenes, Marek Mazur, Development Manager at KantanMT to find out about the great features, benefits and the impetus behind implementing KantanTranslate.

Continue reading

Is Pokémon Go Taking Over the World?

KantanMT and Pokemon GoLike the rest of the world, we have joined the Pokémon Go craze, with many of us here at KantanMT searching for Pokémon characters during lunch or after a day in the office. Of course, it goes without saying that we have our own Whats App group, aptly named ‘Poke’ to share our progress throughout the game, each of us playing in different languages.

Continue reading

MT Trend: Fully Automated Translation Workflows Become a Reality in 2016

Shopping Online Background
The age of automatic translation worlfow

The innovative Machine Translation features released by KantanMT, along with our contribution towards improving automated translation workflow has earned us the reputation for being thought leaders in the industry. A few months back, we released a white paper on what global companies can expect to see in 2016 for Machine Translation (MT).  Continue reading

Guest Post: Mike Miranda – The Importance of Self Service with Data Discovery Tools

Business IntelligenceWhen we’re talking about Business Intelligence, self-service is an approach to data analytics that plays a vital and extremely beneficial role within an enterprise because it allows for immediate decision making.  No-wait decision-making is a enormous contributor for a company’s bottom-line.  Self-service allows business users to retrieve, interact and collaborate with company information without having to rely on IT assistance.

Thanks to self-service, IT personnel can focus their energy on more large-scale responsibilities that benefit the entire enterprise, like setting up the data warehouse and data marts underpinning the BI system, for example, while other team-members can work more strategically and efficiently. Quality data preparation tools are imperative to the independence of business users and integrated tools allow users to operate, analyze, change and calculate data sets quickly using GUI’s to alternate between data prep and visualization screens with just one click.

BI is becoming more intertwined with self-service which should be no surprise since it enables data analysis to be more streamlined and keeps companies optimally responsive, efficient and agile.  Self-service data-discovery tools allow decision-makers to tap into the information they require which enhances their success.  Self-service also helps a company to realize reduced administrative burdens, shortened timelines and the emergence of deeper insights.

Self-service acts as an enterprise’s coveted ally for several reasons:

Continue reading

Machine Translation Trend: Translation Cycles Instead of One-Off Projects

KantanMT recently published a white paper on what global companies can expect to see in 2016 for Machine Translation (MT). The MT industry is rapidly charrows-151433_1280anging and moulding itself to the technical needs and globalization requirements of the present day. Our white paper puts forward six major MT trends that all businesses need to heed in order to stay relevant and ahead of their competitors.

Continue reading

Machine Translation Trend in 2016: The Age of Automatic Workflows and More Collaboration

2016Trends_1_ImageKantanMT recently published a brand-new white paper on what global companies can expect to see in 2016 for Machine Translation (MT). The MT industry is rapidly changing and moulding itself to the technical needs and globalization requirements of the present day. Our white paper puts forward six major MT trends that all businesses need to KNOW in order to stay relevant and ahead of their competitors.

Continue reading

Machines to the Rescue Once Again in Medicine: How can Machine Translation Contribute to Healthcare?

A few weeks ago we mentioned how the Machine Translation market is expecteMedicined to reach USD 983.3 million by 2022. In yet another Industry Global forecast, it was announced that the Natural Language Processing (NLP) Market for the Healthcare and Life Sciences Industry is projected to grow up to USD 2.67 billion, almost doubling the current value of 1.10 billion. In this post, we will discuss the present state of arts of Machine Translation in Medicine, Healthcare and Clinical Practices, and at the same time delve into other recent innovations in technology that can enhance the language industry within Healthcare.

“My Doctor can surely tell me what’s wrong with me in my language?”

The short answer is – no, a healthcare provider may not always be able to communicate in your local language – especially if you are travelling or in another country. About 1 in 50 patient’s visit to the doctor will require an interpreter, and thus, translated content or verbal translation is essential for the contemporary Healthcare and Life Sciences Industry. For a more detailed and enlightening view of this issue, read this article on Machine leaning for medicine and this study on healthcare interpreting.

Translated content or verbal translation is essential for the contemporary Healthcare and Life Sciences Industry

The fact of the matter is that the needs of the Healthcare industry goes beyond mere point-of-care healthcare by doctors and extends to medical documents, web medical help, insurance claims forms, patient records, educational materials, studies and papers, warnings, IVR scripts to just name just a few. This evidently increases the challenges faced by the Healthcare industry. One of our major partnersCNGL Centre for Global Intelligent Content  carried out extensive research in medical care to create a search system that allows users to access biomedical data from a variety of different sources. You can read more about the project in their blog.

So what’s the answer?

Why, Natural Language Processing (NLP) and Machine Translation (MT), of course! The type of NLP solutions for the Healthcare Industry can be broadly categorised into rule-based, statistical, and hybrid NLP solutions. Essentially, this is similar to Machine Translation categories, and works on the same ground rules. The Rule-based NLP technologies work on the basis of certain set of rules provided by humans. The statistical NLP solutions incorporate high end technologies such as machine learning, use the cause-and-effect relationship of language to derive a solution, and the hybrid NLP is the combination of both rule-based and statistical NLP technologies.

How can Statistical Machine Translation Help (SMT)?
Machine Translation can help the Healthcare Industry by automatically translating text or speech in one specific source language into another target language. Statistical Machine Translation (SMT) will translate a given string in the source text into a string in the target language. Simply put then, what SMT systems like KantanMT do is, among all possible target strings, the system selects the string with the highest probability match. Modern SMT is based on the intuition that a better way to compute these probabilities is by considering the beKantanMT Machine Translationhaviour of phrase or sequences of words. In addition to the translation model, SMT systems use a language model, which is usually framed as a probability distribution over strings that attempts to reflect how likely a string is to occur in a particular language.

Building an SMT system requires written and high computational resources with a huge number of parallel corpora between source and target languages at the sentence level. This corpora building can often be a challenging task, especially in Healthcare industry where a huge variation in Named Entities is possible. While we will discuss the challenges with MT in Healthcare in a little more detail in the next section, it should be sufficient in this section to note that the SMT quality depends largely on the language pair of the specific domain being translated. As such, though the need for Machine Translated content in Healthcare cannot be denied, its credibility and increased usage in the vertical can only be expedited with a more robust training data for the engine to “learn” from. KantanMT is a cloud-based, Customised SMT system, which inherently lends itself perfectly to this sort of machine learning or training.

To know more about how the Customised Machine Translation (CMT) by KantanMT can help you, ask for a demo today and shoot a mail to


Addressing potential challenges and pitfalls

First things first: Machine Translation as it stands today cannot perform without the help of human translators. So why should the Healthcare industry still use MT, or indeed, why does the Research and Markets study estimate a rise in the use of MT in the industry?

Simple answer: Content explosion! The Healthcare and Life Sciences Industry as it stands today cannot cater to an increasingly globalised world that required medical help, without the aid of MT – indeed, it is simply not feasible. Having mentioned that, we will quickly discuss the potential pitfalls and solutions of using MT, before rounding off with a look at the potential future of this industry.

  • Machine translation may lead to misunderstanding in Healthcare in the case of inaccurate translations. As such, if MT is being used, Healthcare experts must be ready to mitigate any misunotebooknderstanding through regular feedback. This feedback/ translation can in turn be used to train the MT engines to translate better for the domain.
  • Back-translation, which involves cutting and pasting translated text back into the translator, might help estimate accuracy and appropriateness of the translation, and this is a best-practice that should be carried out often in the Healthcare industry to avoid potentially risky situations.
  • The risk of misunderstanding increases with a patient with low literacy and limited levels of health education. Once again, in such cases, it is important that a trained human translator post-edits the MT output.

The call to action for the Healthcare industry right now then is to ensure that there is enough good quality legacy training data for engines to get “smarter” 

Final words

Even though MT is already being used extensively in the Healthcare industry and clinical settings, medical organisations must be extremely cautious about the application of the translated content. Machine Translation needs to be incorporated in the Healthcare industry, but raw MT output can’t be utilised as the final product. An expert translator should review the content before patients can benefit from the translation.

Because of the boom in content in the Healthcare industry (be it research materials or clinical content), MT is rapidly emerging as an accessible supplementary to communication in the area. However, the performance of the engine remains imperfect and can vary greatly between language pairs. The call to action for the Healthcare industry right now then is to ensure that there is enough good quality legacy training data for engines to get “smarter” and create a data pool that can help MT content be more relevant, precise and useful to the vertical.

To talk more about how the Customised Machine Translation (CMT) by KantanMT can help you, ask for a demo today and shoot a mail to



“Machine Learning for Medicine – Idibon.” Idibon. N.p., 29 May 2013. Web. 20 Oct. 2015.

“Machine Translation in Medicine. A Quality Analysis of Statistical Machine Translation in the Medical Domain.” Machine Translation in Medicine. A Quality Analysis of Statistical Machine Translation in the Medical Domain. N.p., n.d. Web. 20 Oct. 2015.

“Natural Language Processing Market for Health Care and Life Sciences Industry by Type, Region – Global Forecast to 2020.” Natural Language Processing Market for Health Care and Life Sciences Industry by Type, Region – Global Forecast to 2020. N.p., n.d. Web. 20 Oct. 2015.

“The MT Industry Is Evolving: At KantanMT, We Are Growing Too!” Web log post. KantanMT Blog. N.p., n.d. Web.

Randhawa, Gurdeeshpal, Mariella Ferreyra, Rukhsana Ahmed, Omar Ezzat, and Kevin Pottie. “Using Machine Translation in Clinical Practice.” Canadian Family Physician. College of Family Physicians of Canada, Apr. 2013. Web. 10 Oct. 2015.

The MT Industry is Evolving: At KantanMT, we are Growing too!

KantanMT The rapidly evolving, dynamic marketplace today has created an enormous spike in the demand for Machine Translation (MT) in a number of industries. According to a new study by Grand View Research, the global Machine Translation market is expected to reach USD 983.3 million by 2022. This is a huge leap from 2014, when the MT market was valued at USD 331.7 million, and this growth projection mirrors a trend in the market. Thanks to globalization, there is an increased demand for cost efficiency in translation, but the amount of linguistic knowledge and time required for translating all the content for a particular business exceeds the capacity of human translation alone.

Key Insights into the Machine Translation Market

Some of the key insights about Machine Translation that the study discusses are summed up here:

  • Statistical Machine Translation (SMT) is a clear winner over Rules Based Machine Translation (RBMT), when it comes to the present market requirement.
  • Globalization and the need to address diverse cultural groups has led to the popularity of translation technology in Asia Pacific, thus opening up new potential markets for MT providers.
  • Proliferation of smartphones and increasing internet penetration is expected to drive MT market growth.
  • Machine translation as a service (MTSaaS) makes use of SMT and is accessible via the web. This allows users to customise their MT engines with their own Translation Memories (TMs).

What this means is that, deploying an integrated MT solution will become a critical success factor for gaining market share in the future.

Potential Challenges

The study reveals major challenges for the MT industry, which includes a lack of quality translations and Quality Estimation (QE) and competition from free translation service providers. Needless to say, a well-rounded back-end knowledge base, along with efficient NLP (Natural Language Processing) capabilities and a scalable model are critical to gaining competitive advantage in the market. The MT providers need to go above and beyond their role as simply providing machine translation services; they need to become solution providers.

How is KantanMT contributing to the MT market?

The KantanMT platform offers massive competitive advantage, not only because we were one of the first entrants in the MT market, but also because thanks to our strategic market insights, we have already identified most of these challenges and developed solutions to address them. As solution providers, we use an intuitive approach that can be summed up in a few words: speed, scalability, simplicity, and security.


In a market where new products and innumerable variants of those products are being developed almost every day, it is important to have on-demand translated content ready to be deployed. KantanMT helps its clients have the first leap advantage over their competitors by translating content on the fly.

KantanMT engines have the capacity to translate 114 million words in a single day and as of 7 September, 2015, we have exceeded 2 billion translated words, with 1 billion words being translated in the last two months itself. User stats September 2015
KantanMT Platform statistics as of 8th September 2015


As a business trying to make its mark in the global MT market, it is extremely important to have a solution that has limitless scalable potential. KantanMT engines with scaling technologies such as the KantanAutoScale are devised to ensure that no matter how sudden the spike in content is, the quality and volumes of translated content will never suffer.

The power of KantanMT’s engine was summed up Tony O’Dowd, Founder and Chief Architect of,

“We are only starting to see the potential growth of the Machine Translation market, and I doubt any other player can operate at this scale as flawlessly.”


Simplicity is at the very core of KantanMT. The company name itself is derived from the Japanese word for simplicity 簡単 (かんたん). KantanMT strives to take the complexity out of the user interface, while powerful MT engines do all the hard work in the back end. Easy to understand analytics can be generated through the KantanMT engines to gather insights into improving engine quality and maintaining translation quality.


Cloud based MT solutions have become the industry norm. However, security concerns are high – especially, if you are in the eCommerce industry or deal with legal information. KantanMT’s multilayered security approach protects and monitors translations ensuring all industry secrets are safe. Unlike a number of open source translating tools, you own the source as well as translated words.

Final words

One of the key findings of the Grand View Research review points out that “strategic joint ventures, coupled with mergers and acquisitions, (which) have been among the key strategies adopted” by major players in the Machine Translation industry. KantanMT recognises the importance of both industry and academic relationships in building a complete MT ecosystem.

With KantanAPI integration, powerful KantanMT engines can be plugged into Translation Management workflows with ease. Our Developer Partners include companies like Kilgray, Memsource and Alchemy Software Development.

We work with a number of Language Service Providers, and some of our Preferred MT Suppliers include Milengo, MediaLocate and more recently Turkish LSP, Transistent. We are proud to have a strong relationship with leading Industry Associations such as the ADAPT Centre, TAUS and EAMT among others. Moreover, our University Partner Program aims to further education in Machine Translation for new industry graduates.

Contact the KantanMT Team, to learn more about the KantanMT platform.

Global Localization Reaches Another Milestone

KantanMT Cloud Machine TranslationAs a team of people with an unbridled passion for innovations in the Machine Translation industry, Monday’s news about Reverie Technologies, a Bengaluru-based startup bagging a $4M investment did not come as much surprise to us. This brilliant news serves to highlight once again that in the ever-changing world of retail marketing and globalization, any business with plans to accelerate their products into global markets needs to localize their content for enhanced user experience. This goes on to drive global revenues and increase brand equity in existing and new markets. Continue reading

Translation Machines in Sci-fi

Richard Brooks, CEO, K International KantanMT
Richard Brooks, CEO, K International

This blog post was written by Richard Brooks. He’s a firm believer that life imitates art, CEO of the UK-based LSP K International, a company specialising in translation services for the legal industry and director of the Association of Language Companies.

Translation Machines in Sci-fi

In science fiction, translation of the potentially infinite number of languages spoken by alien species presents a dilemma. How to deal with communication between interplanetary species without resorting to contrivance, or spending the first twenty minutes of each episode’s dialogue clumsily showing characters learning one another’s diphthongs?

The notion of a ‘universal translator’ emanated from Murray Leinster’s novella First Contact, published in 1945 (and clearly that isn’t the only debt Gene Roddenberry owes to Leinster). It’s a greatly helpful – borderline miraculous, in fact – convention of sci-fi: a technological solution to the language barrier, leaving more time for the actual narrative to unfold in one language, typically English.

With the incredible advancements in technology we’re witnessing at the moment such as Microsoft’s pilots of a Skype Translator and the industry leading work KantanMT is achieving in this area, are we seeing the beginnings of live translation – well ahead of Star Trek’s 22nd century deadline? In the meantime, let’s take a look at five of sci-fi’s finest translation machines, which beat anything real-life technology can offer – for now.

KantanMT Blog, Universal Translator

1. Star Trek: Universal Translator

An important part of Star Trek’s near-utopian vision of the future is the Universal Translator. Translating any language into another even while a person is speaking, this exceptionally handy tool means Starfleet craft in any quadrant of the galaxy can speak to new life and new civilizations without confusion.

Voiced by Star Trek creator Roddenberry’s widow Majel Barrett until her death in 2008, the development of a universal translator was, in the Trek universe, a portent of Earth’s cultures achieving universal peace. It’s difficult to imagine Google Translate having the same impact.

This convenient concept has been often copied, and occasionally parodied: in Futurama, everyone in the universe speaks English, rendering Professor Farnworth’s one successful invention – a translation device – useless, as it merely translates English into the dead language, French!

2. The Hitchhikers’ Guide to the Galaxy: the Babel Fish

Some sci-fi plays with the concept in less serious ways. In Douglas Adams’ H2G2, to help Arthur Dent deal in some small way with anything that goes on around him, inserted into his ear is a Babel Fish, memorably described by the Guide as “small, yellow, leechlike and probably the oddest thing in the universe.”

The science (such as it is) behind the Babel Fish is that it can absorb the frequencies of outside speakers, and a translation is secreted by the fish into the hearer’s brain via his or her ear canal. In a witty reversal of Star Trek’s idealistic Federation, Adams reveals that, by allowing everyone to understand one another, the Babel Fish has actually caused more war than anything else in the universe.

3. Farscape: Translator microbes

In science fiction, as in reality, it is the individual idiosyncrasies of languages which are trickiest to master. When people in the UK from a hundred miles apart may speak different languages, not to mention a range of different dialects and accents, can auditory translation really be so smooth?

One series to acknowledge this is Farscape, where astronaut John Crichton is injected with bacteria-sized ‘translator microbes’, which are injected into – and colonise – his brain. The microbes work to make their host understand any spoken information in any language – except idioms are translated literally. This leads to a great deal of confusion for John, and opportunities for humour for the audience (all jokes are language, after all) – and also perhaps renders these microbes a more realistically-limited translator technology.

4. Doctor Who: The TARDIS’ Translation Circuit

As well as being telepathically linked with the Doctor, and granting the ability to travel to any time or place in history and the future, the TARDIS’ telepathic field is used to automatically translate what the Doctor and any companions hear or read into a language which they can understand.

While wonderfully convenient, the mind-meld involved does mean that the translation circuits won’t actually work when the Doctor is unconscious – not an outright impossibility. Also, because translations are time specific, ancient civilization won’t understand neologisms – and, neatly, the Romans have never heard the word ‘volcano’ – because they’ve not lived to see an eruption.

5. Star Wars: C-3PO

Luke Skywalker is the ultimate sci-fi everyman: he is every bit as much in need of a guide to the universe he finds himself in as the viewing audience are. Reinforcing this are his guides, C-3PO and R2D2, who Luke needs with him – despite their obvious drawbacks as travelling companions – because C-3PO is programmed with millions of languages, everything from Ewok to R2’s bleeps and whistles.

When the franchise returns with The Force Awakens later this year (which most fans will rightly consider the fourth, rather than seventh, Star Wars movie), C-3PO’s translation abilities are sure to make him at least partially useful to have around.

The KantanMT team say a big Thank You to Richard for a very savvy post on translation machines in science fiction.

Richard (@RichardMBrooks) will join Tony O’Dowd, (@TonyODowd1) KantanMT Founder and Chief Architect alongside other Language industry heavyweights at the ATC Annual Conference in the Old Trafford Stadium on 24th and 25th September 2015. Register here to attend the conference. 

KantanMT at ATC Conference

If you want to learn more about Machine Translation, send us email ( with your questions and we will be happy to answer them!