The Fastest Machine Translation Framework Marian Boasts New and Impressive Features
Experts from Tilde, University of Edinburg, and Unbabel have improved the very popular automated neural translation toolkit Marian.
Experts from Tilde, University of Edinburg, and Unbabel have improved the very popular automated neural translation toolkit Marian.
University of Edinburgh’s Kenneth Heafield joins the Pod to discuss translation efficiency, quality research, and industry vs. academia. Plus: Anna Wyndham on 10 areas where translators remain essential experts in the loop.
European Live Translator (ELITR) takes speech-to-speech translation one step further, backed by the academe, private sector, and government.
The most-cited neural machine translation research papers show how NMT came to dominate the field — and how academia and industry’s interests have evolved.
Facebook has been granted a patent for its machine translation quality evaluation system, which relies on user engagement data to decide which translation users prefer.
Slator’s inaugural comprehensive language industry market report. It examines total market size, the 10 main end-buyer industries, competitive landscape, productivity tech, NMT and much more.
Researchers led by machine translation pioneer Philipp Koehn examine how interactive translation prediction compares to MT post-editing when powered by neural instead of statistical MT.
Research into neural machine translation in 2018 is exploding, with April 2018 being the busiest month ever for NMT, as Big Tech companies from Google to Facebook to Amazon go full throttle on multiple areas of research.
In 2015, four leading European institutions and companies set out to solve machine translation’s four main problems: training, context, scalability, and data collection. After a brief scare when Google Translate went neural, the project is now in beta and set for enterprise-grade release in Q4 2017.
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