neural 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. Mercedes García-Martínez, who has a PhD in computer science with a specialization in neural machine translation research, has recently joined our team. 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 […]

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 […]

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 […]