The readers have spoken on topics ranging from governments supporting linguist training and education, post-editing machine translation, current demand for Asian languages, and the 2019 outlook
Language service provider RWS tells investors at capital markets event about how it is integrating Moravia and informs about the results of a pilot project to deploy MT post-editing in production in its patent translation division.
Shopify’s Content and Localization Manager, Giulia Greco, shares how the multi-channel ecommerce company will have localized six million words by the time 2018 ends, and why translation was the easy part.
ABBYY licenses the Xerox brand in joint launch of curious hybrid between online translation platform and machine-translation-enabled copy machine. Xerox’s sales force will have to work hard to push this one.
Predictive typing, no more middlemen, visualized app translation, machine translation edited by the crowd, and more. What is shaping tomorrow’s language industry. And are the incumbents ready for what’s coming?
ISO 18587 is the standard followed by organizations offering machine translation (MT) and post-editing services including Argos Multilingual
LSPs moving toward hourly rates for linguists? Edit distance a viable metric long-term? Are regulations important to translation demand? Will Rev recover from bad press over transcriptionist pay cuts?
As the language industry becomes more and more competitive, what are universities doing to ensure that their translation students are ready to enter the marketplace?
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.
Germany-based language service provider lengoo secures EUR 6.0m in Series A funding, targets scale with NMT and post-editing for mature enterprise customers.
Characterizing post-editors based on their keystrokes, mouse activity, and other editing actions can help predict speed and, eventually, quality, says a new paper by Unbabel researchers.
The apex court is said to be using “translation software” to translate judgments into six Indian languages — a first in India, where the language of the law is still largely English.
Post-editing machine translation versus unaided human translation from scratch — new research reveals how the output differs.
Slator’s readers give their take on translation devices, per-hour word output for post-edited MT, post-editing versus interactive prediction, and M&A activity in 2019.
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.
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.
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.
Facebook experiments with post-editing to improve its neural machine translation system. The QuickEdit system supposedly improves machine output by learning from post-editors by simply rejecting words in a translation that don’t work.
Wizi cofounder Paulo Dimas named Head of Product at Unbabel based in Lisbon, CMO says company now has 400 paying customers
Perfect domain name vs. WhatsApp-like user interface: how Translate.com and Stepes are trying to conquer the long tail of translation demand through crowdsourcing.
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