Team of Amazon AI researchers combines various deep-learning models to build automatic dubbing system. Viewer feedback reveals unnaturalness of speaking rate as main problem.
Efficiency boost for tens of thousands of translators as MMT launches the first ever adaptive neural machine translation plugin for two of the most widely used translation productivity tools, SDL Trados Studio and MateCat.
Europe continues to ramp up research in language technology. The number of papers published on machine translation in an academic journal has reached the highest number in more than a decade.
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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