KantanOfficeMT™ Explained: Interview with Seosamh, Software Developer

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We are very excited to bring to our readers another new interview with one of our KantanMT Feature Developers. This time we interviewed Seosamh Ó Cinnéide, following the launch of KantanOfficeMT™. Seosamh is an Associate Software Development Engineer at KantanMT, and we asked him a few questions to find out more about the features and benefits of using KantanOfficeMT.
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A Big Thank You to Everyone Involved in the Coastal Flag Challenge for Translators without Borders

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Last weekend one of the most important things we discovered is that folks working in the language industry are some of the coolest, smartest, most fun-loving yet hard-working people. They are also extremely generous. After attending the LavaCon and LocWorld31 Conferences, teams and members from various companies all around the world took up the Coastal Flag Challenge to hike along the Howth trail to raise money for Translators without Borders (TWB), a non-profit organisation that works to close critical language gaps that hinder humanitarian efforts worldwide. They support the work of hundreds of organisations in the areas of crisis relief, health and education. Continue reading

New Feature Release: Interview with Louise Faherty, Project Manager, Professional Services Team on features and benefits of KantanLQR™

Following KantanMT’s announcement of the roll out of the much-anticipated KantanLQR™ platform to all its Partners worldwide, Louise Irwin from Digital Marketing Team caught up Louise Faherty, Project Manager, Professional Services, KantanMT to talk about the features, benefits and the impetus behind creating the tool. 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.

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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.

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A Trip down Memory Lane: KantanMT in 2015

KantanMT Year in ReviewWhile chatting over a mouthful of mince pies, some tourtière and a few classy glasses of mulled wine this week, we at KantanMT were suddenly struck by the realisation that 2015 was perhaps one of the most sensational, successful and eventful years for us in the company! And the fact is, we can’t wait to start working on everything that we have planned for 2016 – we are certain that the new year is going to be even more exciting for us.

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All your Burning Questions Answered! How Machine Translation Helps Improve Translation Productivity (Part I)

Part I

We had so many questions during the Q&A in our last webinar session ‘How to Improve Translation Productivity‘ by the KantanMT Professional services team, that we decided to split the answers into two blog posts. So, if you don’t find your questions answered here, check out our blog next week for the remaining answers. 

KantanMT_ComputersInternet today is experiencing what is generally referred to as a ‘content explosion!’ In this fast-paced world, businesses have to strive harder and do more to stay ahead of the game – especially if they are a global business or if they have globalization aspirations. One fool-proof way in which a business can successfully go global is through effective localization. Yet, the huge amount of content available online makes human translation for everything almost impossible. The only viable option then in today’s competitive online environment is through the use of Machine Translation (MT).

On Wednesday 21st October, Tony O’Dowd, Chief Architect of KantanMT.com and Louise Faherty, Technical Project Manager at KantanMT presented a webinar where they showed how Language Service Providers (LSPs)  (as well as enterprises) can improve the translation productivity of the team, manage post-editing effort and easily schedule projects with powerful MT engines. Here is a link to the recording of the webinar on YouTube along with a transcript of the Q&A session.

The answers below are not recorded verbatim and minor edits have been made to make the text more readable.

Question: Do you have clients doing Japanese to English MT? What are the results, and how did you get them? (i.e., do you pre-process the Japanese?)

Answer (Tony O’Dowd): English to Japanese Machine Translation (MT) has indeed always posed a challenge in the MT industry. So is it possible to build a high quality, high fidelity MT system for this language combination? Well, there have been quite a few developments recently to improve the prospect of building effective engines in this language combination. For example, one of the latest changes we made on the KantanMT platform for improving the quality of MT is by using new and improved reordering models to make the translation from English to Japanese and Japanese to English much smoother, so we deliver a higher quality output. In addition to that, higher quality training data sets are now available for this language pair, compared to a couple of years ago, when I had started building English to Japanese engines. Back then it was really challenging. It is still requires some effort to build English to Japanese MT engines, but the fact that there’s more content available in these languages makes it slightly easier for us to build high-quality engines.

We are also developing example-based MT for these engines and it so far this is showing encouraging signs of improving quality for this language pair. However, we have not started deploying this development on the platform yet.

KantanMT note: For more insights into how you can prepare high-quality training data, read these tips shared by Tony O’Dowd, and Selçuk Özcan, co-founder of Transistent Language Automation Services during the webinar ‘Tips for Preparing Training Data for High Quality MT.’

Question: Have you got a webinar recorded or scheduled, where we could see how the system works hands-on?

Answer (Tony O’Dowd): If you go on to the KantanMT website, we have video links on the product features pages. So you can actually watch an explanation video while you are looking at the component.

We work in a very visual environment, and we think videos are a great way of explaining how the platform works. And, if you go on to the website, on the bottom left corner of the page, you will find our YouTube channel, which contains videos on all sorts of topics, including how to build your first enginehow to translate your first document and  how to improve the output of your engines.

If you click on the Resources menu on our site, you can access a number of tutorials that will talk you through the basics of Statistical Machine Translation Systems. In other words, explore the website and you should find what you need.

KantanMT note: Some other useful links for resources are listed below:

Question: Do you provide any Post-Editing recommendations or standards for standardising the PE process? You said translation productivity rose to 8k words per day – this is only PE, correct?

Answer (Tony O’Dowd): I will take the second question first! The 8,000 words per day is the Post-Editing (PE) rate, yes. It is not the raw translation rate. In Machine Translation, everything comes out pretranslated. So this number refers to the Post-Editing effort – like insertions, deletions, substitution of words, and so on that you need to do to get the content to publishable quality.

Louise Faherty: What we recommend to our clients is that when it comes to PE, they should try to use MT. A lot of translators who are new to using MT will try and translate manually, which is a natural tendency, of course. But what we advise our clients is to copy and paste the translation (MT) in the engine and use the MT. The more you use MT and the more you Post-Edit, the better your engine will become.

Tony O’Dowd: I will add something to Louise Faherty ’s comments there. The best example of PE recommendations that I have come across is provided by a group called TAUS. They are at the pivot of educating the industry on how to develop a proficiency in PE.

Subscribe to TAUS YouTube channel here.

Question: What do ‘PPX’ and ‘PEX’ stand for (as abbreviations)?

Answer (Louise Faherty  and Tony O’Dowd): PEX stands for Post-Editing Automation. PEX allows you to take the output of an MT engine and dynamically alter that. When would you need to use PEX? Suppose there is a situation where your engine is repeating the same error over and over again. What you can do in such cases is write a PEX file (developed in the GENTRY programming language). This allows the engine to look for patterns in the output of the engine and to dynamically change that in the output.

For example, one of our French clients did not want to have a space preceding a colon mark in the output of their MT (because this was one of their typographical standards and repeated throughout the content). So we wrote a PEX rule that forced a stylistic change in the output of the engine. This enabled the client to reduce the number of Post-Edits substantially.

PPX stands for Preprocessor automation. You can use PPX files for to normalise or improve the training data. It is based on our GENTRY programming language which is available to all our clients for free.

In short then, PPX is for your training data, while PEX is for the actual raw output of your engine.

For more questions and answers, stay tuned for the next part of this post!

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.

Speed

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.

KantanMT.com User stats September 2015
KantanMT Platform statistics as of 8th September 2015

Scalability

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 KantanMT.com,

“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

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.

Security

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, info@kantanmt.com to learn more about the KantanMT platform.

Improving workflow integration and efficiency with KantanAPI

What is the KantanAPI?

KantanAPI enables KantanMT clients to interact with KantanMT as an on-demand web service. It also provides a number of different services including translation, file upload and retrieval and job launches.

With the KantanAPI  you not only have the opportunity to integrate KantanMT into your workflow systems but also the ability to receive on-demand translations from your KantanMT engines. All these services make the experience with Machine Translation as seamless as possible.

Accessing KantanAPI

Please Note: The API is only available to KantanMT members in the Enterprise Plan.

To access the KantanMT API you will first need your ‘API token’. This token can be found in the ‘API’ tab on the ‘My Client Profiles’ page of your KantanMT account.

Once you have your token you can use the API in a number of ways

  1. Using the API tab on the ‘My Client Profiles’ page in the KantanMT Web interface
  2. Using the REST interface via HTTP GET or POST requests
  3. Using one of our various connectors, which are built using our KantanAPI

For more details on implementing your API solution via the REST interface, please see the full API technical documentation at the following link:

How to use KantanAPI?

Login into your KantanMT account using your email and your password.

You will be directed to the ‘My Client Profiles’ page. You will be in the ‘Client Profiles’ section of the ‘My Client Profiles’ page. The last profile you were working on will be ‘Active’.

If you wish to use the ‘KantanAPI’ with another profile other than the ‘Active’ profile. Click on the profile you wish to use the ‘KantanAPI’ with, then click on the ‘API’ tab.

API tab

You will be directed to the ‘API Settings’ page. Now click on the ‘Launch API’ button.

Launching API

A ‘Launch API’ pop-up will now appear on your screen asking you ‘Are you sure you want to launch the API?’ Click ‘OK’.

launch Pop-up alert

The ‘API Status’ will now change from ‘offline’ to ‘initialising’, the ‘Launch API’ button will now change to ‘Launching API’ .

Launching API

When your KantanAPI launches the ‘API Status’ will now change from ‘initialising’ to ‘running’, the ‘Launching API’ button changes to ‘Shutdown API’ and you should now be able to click on the ‘Translate’ button.

API running

Type the text you wish to translate in the text box and click on the ‘Translate’ button.

Translating

The translated text will now appear in the ‘Translated Text’ box. If you wish to make any changes to the translated text simply place the cursor inside the ‘Translated Text’ box and make the changes. Save these changes by clicking the ‘Retrain Engine’ button.

Retrain Engine

Test if your engine was successfully retrained by clicking the ‘Translate’ button. The retrained text will now appear in the ‘Translated Text’ box.

If you don’t wish to retrain your engine and you are happy with the translated text in the ‘Translated Text’ box. You may continue translating other text or shut down your KantanAPI by clicking the ‘Shutdown API’ button.

When you click the ‘Shutdown API’ button a pop-up will now appear asking you ‘Are you sure you want to shout down the API?’ Click ‘OK’.

Shutdown Pop-up alert

The ‘Shutdown API’ button will now change to ‘Terminating API’, the ‘API status’ will now change from ‘running’ to ‘terminating’ and you shouldn’t be able to click on the ‘Translate’ or ‘Retrain Engine’ button.

Terminating API

You will now be directed back to the initial screen on the API Settings page.

API settings page

 

Additional Support

KantanAPI™ is one of the various machine translation services offered by KantanMT to improve  productivity for our clients and also enable them to be more efficient. For more information on KantanAPI or any KantanMT products please contact us at info@kantanmt.com.

For more details on the KantanMT API please see the following links and the video below:

Identifying Translation Gaps and Managing Machine Translation with KantanTimeLine™

What is Gap Analysis and Kantan TimeLine ?

Gap Analysis identifies and reports any untranslated words in the training data set and allows you to take preventive measures quickly by fine tuning training data and filling data gaps.The KantanTimeLine™ provides a chronological history of activities for each engine and uses version control for precise management of released and production-ready engines.

Using Kantan TimeLine and Gap Analysis:

In KantanBuildAnalytics, click the Gap Analysis tab to see the amount of untranslated words that remain in the generated translations. You will be directed to the Gap Analysis page, where you will see a breakdown of any gaps in your training data.

Gap Analysis tab in KantanMT

A table appears with 3 headings: ‘#’, Unknown Word, Reference/Source, KantanMT Output. Under those headings  you will find details of any untranslated words, their source and the KantanMT Output.

KantanMT Gap Analysis Table

Click Download to download your Gap Analysis report.

Download Gap Analysis KantanMT

Note: You can also click the Timeline tab to view your profiles’s Timeline, which is essentially a record of the changes you have made on your engine.

TimeLine Image

This is one of the many features provided in KantanBuildAnalytics, which aids Localization Project Managers in improving an engine’s quality after its initial training. To see other features used in KantanBuildAnalytics suite please see the links below.

Contact our team to get more information about KantanMT.com or to arrange a platform demonstration, demo@kantanmt.com.