neural machine translation

NMT versus SMT results in Japanese

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 […]