Machine translation

Researcher in neural machine translation: Mercedes García-Martínez

Pangeanic is a company in constant technological development: our award-winning R&D is focused on AI and Neural Machine Translation research and development to offer our customers the best quality translations and innovative services. Our team has recently been joined by Mercedes García-Martínez, PhD in specialized computer science and researcher in neural machine translation. Mercedes did her PhD at the computer lab of the University of Le Mans in France. Her thesis, titled “Factored Neural Machine Translation“, was one of the first in the world to investigate neural translation models and to apply factorial models to this type of machine translation for the first time. In general, it consists of helping to improve translation quality, through linguistic knowledge, increasing the available vocabulary without having to increase the size of the neural network. She has also taken specialized courses in neural networks, such as the one given in Montreal, Canada at the prestigious MILA laboratory and another […]

Protecting The Integrity Of Mental Health Documents In Translation

Translating medical health documents is part of the global language services industry that is worth more than $43 billion in 2017 and is expected to increase to $47.5 billion in 2027. Alas, translation is not a straightforward process. Protecting the integrity of mental health documents in translation has become a major concern for medical device companies and suppliers of translation services to healthcare companies. The main concern is that the integrity of information that is reworded might not reflect the original purpose of the documents. The type of translation method that is employed is an important factor that determines the outcome of the interpreted material. There are several divergent views as to how mental health documents should be interpreted. One is the traditional back translation technique and the other is the usability method. Deciding which approach works the best is dependent on the target audience and purpose of the material. Pangeanic recently won […]

The Future of Machine Translation

It’s an exciting time for translators indeed, with December 2017 seeing the launch of two AI systems able to teach themselves any language. According to Global Market Insights, the translation industry will have a $1.5 billion net worth by 2024, with “the ability to translate different languages according to customer preferences and the lack of existing translator for several specialized fields and language combinations providing tremendous growth opportunities for the industry.” This is good news both for individual translators and translator tech developers. Both will be called upon to deliver increasingly specialized translation solutions to fulfil an ever-growing global demand. Technology does not Aim to Replace Translators Before delving into the machine translation systems that will be dominating the industry, it is important to understand that these systems are not meant to replace human translators. For example, Korea has one of the highest robot populations in the world and hardly 0 unemployment. Higher automation creates […]

Disintermediation – The Uber of Translation and iADAATPA open source multi-MT platform

by Manuel Herranz Speaking at two conferences in two very different scenarios and to two very different audiences gives you the precious opportunity to get a taste of what the market thinks, the fears and the wishes. By market I mean people that represent business, companies or represent themselves but they have an influence on what others think in their profession. In my case, this is happened in Athens at the Elia Together conference and at Gala Boston recently. Although the presentations were targeted at two very different groups, they shared some common ground. Both audiences contained professional translators and linguists and representatives of translation companies. The presentation in Athens dealt more with the future of translation as a profession, some marketing development tips and a short summary of our iADAATPA open source multi-MT platform project which inevitably led to the question of “How does neural machine translation work”?. The presentation […]

Our Nordic Translation Industry Forum Blog diary!

by Garth Hedenskog From Wednesday, the 22nd until Friday the 24th of November, Pangeanic traveled north to Helsinki to attend our first Nordic Translation Industry Forum! And what an amazing event it was. Let’s start off by saying that Helsinki is a stunning location for business or pleasure. The team was greeted by light snow and a high of 1ºC for most of the 4 day stay! Garth Hedenskog (our sales director) and Alex Helle (our chief research and developer) were lucky enough to go this year. This was naturally a very popular event/destination to attend with a lot of staff at Pangeanic very eager to go! Here is Garth and Alex trying to look busy with at the interpreting challenge, they didn’t fool anyone! Garth and Alex of course didn’t just go for the beautiful scenery, adventure and crisp fresh Nordic air, they went to showcase Pangeanic’s technology, see […]

The Pangeanic neural translation project

The last few months have been extraordinarily busy at Pangeanic, with a focus on the application neural networks for machine translation (neural machine translation) with tests into 7 languages (Japanese, Russian, Portuguese, French, Italian, German, Spanish), the completion of a national R&D project (Cor technology as a platform for translation companies offering an integrated way of analyzing and managing website translation and document analysis), the integration of CAT-agnostic translation memory system ActivaTM into Cor and our neural engines, and the award by the European Union’s CEF (Connecting Europe Facility) of the largest digital infrastructure project to build secure connectors to commercial MT vendors and the EU’s own machine translation service (MT@EC) for public administrations across Europe. Leading machine translation developers such as KantanMT, Prompsit, Tilde and our PangeaMT join forces with consulting company Everis to build IADAATPA, a system that will intelligently work on domain adaptation and the selection of […]

TAUS Tokyo Summit: improvements in neural machine translation in Japanese are real

Not that business plans are written in stone any longer, but efforts to provide an insight by experts are always welcome. TAUS Tokyo Summit provided a much awaited for set of good news about perceived human translation improvements in neural machine translation in Japanese. English-Japanese was a well-known difficult language pair for rule-based machine translation and statistical machine translation provided a really awful experience for many Japanese audiences. It has historically been one of the hardest language combinations to automate. It seems that neural machine translation may be the answer. Day 1 – Where is the translation industry heading? Jaap began by summarizing the latest meeting of thought leaders in Amsterdam who met in Amsterdam in order to brainstorm a potential landscape and priorities for the language industry in the five years. If machine translation hype was at its peak five years ago with statistical machine translation and all sort […]

web and spider crawling down

A web of problems: Why Google Translate and website translation can’t marry

It is not news that machine translated websites are penalized by search engines. Google has developed its technologies on the back of reliable bilingual website crawling and freely available public data. After ditching rule-based engines (Systran) back in 2006, it embarked on a mission to use statistical machine translation (SMT) as a byproduct of its own data analysis. Websites that use machine translation to inform users are crawled and aligned, but those alignments provide data that adds dirt (read: uncertainty) which worsens the probabilities and hence the output (read: the translation). That is why Google Translate and website translation can’t marry. A machine translated website will be penalized by Google, for it is dirty. It is also a proof of laziness on the part of those responsible. The search giant wants to analyze natural, human data. We recently bumped into an article on Slator.com that got our feathers all aflutter. […]

Deep learning – The day language technologies became a Christmas present

It is said the third Monday every January is the saddest day in the year. It does not take deep learning to feel so. A long vacation period has ended. No sight of another one until several months away. Overspent, overstuffed, with no more presents to exchange, with winter settling in the Northern hemisphere and missing the drinks and chocolates that made our sugar levels go sky high, many start booking holidays in the sun. Let’s turn the clocks back to Christmas and we will remember the last few weeks as the Christmas when language technologies made it to the top of the list. Millions of people, literally, have opened boxes whose content was an electronic assistant with a rapidly improving ability to use human language. There are two main products: Amazon’s Echo, featuring the Alexa digital assistant, which sold more than 5m units. In essence, Echo is a desktop […]

Maxim Khalikov from Booking.com

Some takeaways from TAUS Summit Portland

TAUS Yearly Summit in Portland was a great event and the largest I have attended so far (and I have been a regular attendee since 2007 in Brussels). The organization has definitely grown from being considered a think-tank to promote the exchange of data for the benefit of automatic translation engine training, to develop useful tools for the industry. There were times when only experts and a few EU officials or managers from large corporations attended. The mixture in the audience and the quality of the keynotes prove that TAUS has grown as a major reference conference for decision makers and translation technology implementers in the language industry far away from service LSP’s conferences. We are going to be postediting and leaving the TM syndrome behind. Translators will need to face the reality and the realm is post-editing – Tony O’Dowd, CEO, KantanMT. Unfortunately, I missed the first day of […]