Please use this identifier to cite or link to this item: http://dx.doi.org/10.23668/psycharchives.2690
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dc.rights.licenseCC-BY-SA 4.0-
dc.contributor.authorvan Genabith, Josef-
dc.date.accessioned2020-01-15T09:09:37Z-
dc.date.available2020-01-15T09:09:37Z-
dc.date.issued2019-11-20-
dc.identifier.citationVan Genabith, J. (2019, November 20). How Machine Translation Works. A whistle-stop tour from the past to the present and future. ZPID (Leibniz Institute for Psychology Information). https://doi.org/10.23668/PSYCHARCHIVES.2690en
dc.identifier.urihttps://hdl.handle.net/20.500.12034/2304-
dc.identifier.urihttps://www.youtube.com/watch?v=8ZV77u9SKdw-
dc.identifier.urihttp://dx.doi.org/10.23668/psycharchives.2690-
dc.description.abstractOver the last few years machine translation has been making tremendous progress, so much so that for certain language pairs and genres human parity (and even super-human performance) has been claimed (and contested). In this talk van Genabith retraces the story of machine translation from rule-based, statistical to neural approaches (RBMT, SMT and NMT). The objective is to present the main ideas underpinning the approaches in accessible terms and, following this, provide a glimpse of what is currently in the labs.en
dc.language.isoeng-
dc.publisherZPID (Leibniz Institute for Psychology Information)en
dc.relation.ispartofZPID-Kolloquium 2019, Trier, Germany-
dc.rightsopenAccessen
dc.rights.urihttps://creativecommons.org/licenses/by-sa/4.0/-
dc.subject.ddc150-
dc.titleHow Machine Translation Works. A whistle-stop tour from the past to the present and futureen
dc.typemovingImageen
dc.typeconferenceObjecten
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