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Neural Machine Translation Quality and Post-Editing Performance ...
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Manual Re-evaluation of Translation Quality of WMT 2018 English-Czech systems
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Abstract:
This data set contains four types of manual annotation of translation quality, focusing on the comparison of human and machine translation quality (aka human-parity). The machine translation system used is English-Czech CUNI Transformer (CUBBITT). The annotations distinguish adequacy, fluency and overall quality. One of the types is Translation Turing test - detecting whether the annotators can distinguish human from machine translation. All the sentences are taken from the English-Czech test set newstest2018 (WMT2018 News translation shared task www.statmt.org/wmt18/translation-task.html), but only from the half with originally English sentences translated to Czech by a professional agency.
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Keyword:
adequacy; fluency; machine translation; manual evaluation; Translation Turing test
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URL: http://hdl.handle.net/11234/1-3209
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Czech image captioning, machine translation, sentiment analysis and summarization (Neural Monkey models)
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Universal Dependencies 2.2
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In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018)
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