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
Academia
How academic institutions educate and shape tomorrow’s business leaders and technologists
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
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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
As interest in neural machine translation reaches new heights — with even Mark Zuckerberg posting about it on his personal Facebook page — academia continues to churn out NMT papers at a record clip; 2017 output already on par with whole of 2016. Continue reading
Research by Oxford Internet Institute on how online consumers react to foreign-language, user-generated reviews reveals that nearly one-third rely on machine translation to make their choice. Continue reading
Harvard and Systran publish a paper on their open-source neural machine translation model, OpenNMT. Research toolkit is a complete NMT implementation. Creators hope it will become the Moses of NMT. Continue reading
“Google, we promise we are not taking you on,” says the Harvard NLP group as a research project draws Systran’s attention and is co-developed into open-source NMT. Systran expects competitors to quickly build products based on the technology. Continue reading
Research into statistical machine translation is fast falling out of favor among the research community as the number of papers published on neural machine translation skyrockets in 2016. Continue reading
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