Microsoft’s “human parity” claims drew skepticism from a team of neural machine translation researchers as they found that much of the research and industry community is looking at the problem from the wrong angle. Continue reading
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Research submissions on neural machine translations ballooned from 91 in the first half of 2017 to 196 in the first half of 2018, although by July 2018 submissions were slowing down. Continue reading
Professor Laura Burian, the new dean of the Middlebury Institute’s Graduate School of Translation, Interpretation, and Language Education, says her priority is to adapt the curriculum to prepare students to lead in a rapidly evolving language and technology market. Continue reading
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Some familiar names helped pushed May 2018 to the top of the charts in terms of neural machine translation research. Meanwhile, the hottest research trends appear to be the race to better quality and translating low-resource, non-Latin languages. Continue reading
US researchers outline how technology could be used to support the work of simultaneous interpreters. They propose analyzing the linguist’s performance on the fly via real-time quality feedback loop and offer help only when the interpreter is struggling. Continue reading
Professor Andy Way, Deputy Director of ADAPT Centre for Digital Content Technology, unpacks quality expectations for machine translation as the language industry increasingly favors neural MT as the new standard. Continue reading
Facebook is inviting the academic community to submit research proposals for a USD 20,000 to USD 40,000, one-year research grant starting June 2018. Facebook research will award up to four research proposals and is open to further research after evaluation. Continue reading
Facebook’s AI Research team delves into the neural machine translation black box and figures out a couple of ways to mitigate performance degradation due to intrinsic and extrinsic “uncertainties.” Continue reading
As long as machine translation is fluent, users are more likely to trust its output, regardless if the translation is adequate. This is the implication of a recent study by researchers from the University of Maryland. Continue reading
With the ambitious goal of achieving natural language understanding by 2030, research institutions in Europe led by the German Research Center for Artificial Intelligence are pushing for the Human Language Project to become an EUR 1bn EU Flagship Project. Continue reading
Making do with less training data, infusing models with more document-level context, and increasing efficiency and reducing power consumption have been high on the agenda of neural machine translation researchers over recent months. Continue reading
US government earmarks USD 14m for research into automated translations of low-resource language material for the intelligence community. System will be able to retrieve info, translate, and summarize in English with capacity to translate 750m words daily. Continue reading
In early September, Copenhagen will become the center of the machine translation universe as hundreds of researchers gather in the Danish capital to learn whose system performs best. Continue reading
Switzerland’s National Science Foundation funds a research project by the University of Zurich to the tune of CHF 0.46m that tackles one of machine translation’s core challenges – the lack of adequate contextualization. Continue reading
Results of a survey among hundreds of machine learning researchers say machines will overtake (amateur) human translators by 2024. Translating film subtitles will take another two years, while cracking an entirely new language Rosetta Stone-style another eight years. Continue reading
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