How academic institutions educate and shape tomorrow’s business leaders and technologists
European Commission names 27 winners of Juvenes Translatores 2020–2021, who worked on translating ‘eyelids drooping,’ ‘scraped together,’ and other challenging bits from a diary entry from the future. Continue reading
MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) derives algorithm to handle lack of training data, making it easier to adopt current machine translation methods. Continue reading
Group led by Princeton Computer Scientist runs large-scale analysis in 41 languages across 10 language families to determine semantic alignment between languages. Continue reading
Association for Computational Linguistics names Best Research Papers of 2020 from a field of more than 3,000 submissions; paper that argues for retiring BLEU is runner-up. Continue reading
European Commission announces 28 winners of 2019–2020 edition of annual competition that draws the best young translators from all over the EU. Continue reading
The world’s largest NLP conference, EMNLP, announces the winners of the 2019 awards for Best Paper, Best Paper Runner-Up, Best Demo Paper and Best Resource Paper. Continue reading
Google has admitted machine translated content is a challenge to ranking algorithms. Researchers at the University of Tokyo may have found a solution: back-translation. Continue reading
As demand for media loc strains suppliers, there is a case for automation. Research finds NMT might be used for subtitles without special training. Continue reading
Post-editing machine translation versus unaided human translation from scratch — new research reveals how the output differs. Continue reading
Study examines impact of machine translation post-editing on productivity of in-house translators at Switzerland’s Migros Bank. Continue reading
Facebook is offering USD 10,000 to USD 50,000 grants to universities to build open source datasets and evaluation platforms to help fight harmful content online. Continue reading
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. Continue reading
The results of two post-editing of machine translation surveys shine a light on the opinions of practitioners (post-editors and LSPs) on post-editing. Continue reading
Real-time terminology assistance for simultaneous interpreters may be well on its way — but will it be truly useful in typical high-stakes environments? Continue reading
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