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.
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 →
The globalised make-up of the car industry, means automated translation is an important tool for those working in the automotive industry. KantanMT has helped clients use Machine Translation to efficiently translate technical documentation, motor part catalogues and how-to manuals, whilst automotive websites, such as ChromeData use KantanMT to translate content, so it can give detailed vehicle info and specifications for thousands of websites and dealerships around the globe.
The automotive industry has always been one of change. That change is leading to fundamental shifts in car technology and how users interact with them. In 2016, a typical car coming off the production line will contain 100 million lines of code. 20 million of those lines of code are required just to run a standard navigation and infotainment system. This increasing complexity inevitably leads to increasing level of customisation.
Changing Automotive Industry
While technology continues to advance, car manufacturers are increasingly looking at it as an area of differentiation. As manufacturers explore ways of delivering superior performance, implementing software that can be updated regularly, similar to that of a mobile phone, will enter mainstream usage in our cars. Technology centric car companies such as Tesla are already utilising such conveniences and it is inevitable more will follow.
KantanMT’s Academic Partner the University of Alcalá (UAH), used the KantanMT platform to teach final year undergraduate students about Machine Translation during the 2015-2016 academic year.
KantanMT.com was used in the course ‘Machine Translation and Post-editing‘, which was taught for the first time in the ‘Degree in Modern Languages Applied to Translation’ in UAH. English and Spanish were used as the main languages used during this course.
We caught up with Professor Cristina Toledo Báez, and in this post she describes her experience of using KantanMT during the course.
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 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 heed in order to stay relevant and ahead of their competitors.
This week, Dr Dimitar Shterionov, Machine Translation Researcher at KantanMT, presented at the Cloud Security workshop conducted by Irish Centre for Cloud Computing and Commerce (IC4). The information-packed workshop, which was a huge success, aimed to draw back the curtain on cloud security and help companies make more informed choices regarding cloud security within their organisation.
In this post we will highlight some of the issues discussed during the workshop as well as the best practices, tools and guidelines that will help decision making for businesses making the move to the cloud.
KantanMT has an ongoing Academic Partnership with Centre for Multidisciplinary and Intercultural Inquiry (CMII) at University College London to accelerate research and learning in the field of Machine Translation (MT). The postgraduate students of the department were able to use the KantanMT platform to update or gain new skills in Translation Technology. With help of the KantanMT platform, the students learnt how to build and customise their own Statistical Machine Translation (SMT) systems in a real world scenario.
16 years ago when the Web was strictly 1.0, Google was but in its nascent state, and there were a mere 361 million Internet users, David Bowie had made one of the most visionary statements about the future of the Internet:
What the Internet is going to do to society is unimaginable
Indeed, with more than 3 billion Internet users today, one can safely accede that Bowie’s prediction has come to fruition.
If you are in the language service industry, you are undoubtedly on the lookout for ways in which you can improve the productivity of your team – more translated words in less time – that’s what drives your clients as well as you. Automated Machine Translation (MT) seems to be the logical step forward in today’s world of content explosion and tightening deadlines. However, for most Language Service Providers (LSPs), the challenge lies in the actual implementation of this sophisticated technology.
For this reason, it is important that no matter what translation management tools you use, it should be integrated with a powerful MT engine that is reliable, scalable, flexible, and can be trained and re-trained constantly for maximum efficiency and quick turnaround times.
In today’s fast-paced world of content explosion on the Internet, the need for translating this organically growing content with the help of machines has become inevitable. While post-editing the machine translated content will always be required, choosing the right MT features will ensure that translators do not spend countless frustrating hours on those edits.
In this Kantanwebinar, The KantanMT Professional Services Team, Tony O’Dowd and Louise Faherty (Quinn) will show how you can improve the translation productivity of your team, and manage effort estimations and project deadlines better with a powerful MT engine.
During this webinar you will learn:
Translation challenges (co-ordinating and managing translation projects)
About the necessity of Machine Translation to be competitive
How KantanMT.com can be integrated with other Translation Management Systems
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.
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.
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 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.
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.