As the language industry transitions to an operating model where the first draft is mostly generated by machines, many are looking for ways to quantify linguists' value-add. Edit-distance can help. 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
NVIDIA Senior Deep Learning Engineer Chip Huyen details progress on MT challenges, including data requirements, sentence-length limitations, and imperfect quality evaluation techniques. Continue reading
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. Continue reading
At SlatorCon London 2019, Systran CEO Jean Senellart outlined the latest in NMT developments, called out some myths from vendors, and pointed out what’s missing from the industry. Continue reading
August 2018 became the busiest month ever for neural machine translation research as more papers call for improved evaluation methods and big tech companies step up the number of submissions. Continue reading
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... Continue reading
When Google’s CEO goes on stage and measures translation accuracy to the third decimal place, it is as good a time as any to take a closer look at the yardstick he uses. A short introduction to BLEU Continue reading
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