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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 English to Irish Machine Translation with Automatic Post-Editing Dowling, Meghan [Verfasser]; Lynn, Teresa [Verfasser]; Graham, Yvette [Verfasser]. - Aachen : Universitätsbibliothek der RWTH Aachen, 2016 DNB Subject Category Language Show details 2 Is all that glitters in MT quality estimation really gold standard? Lynn, Teresa; Baldwin, Timothy; Eskevich, Maria; Graham, Yvette; Tounsi, Lamia; Dowling, Meghan In: Graham, Yvette, Baldwin, Timothy, Dowling, Meghan orcid:0000-0003-1637-4923 , Eskevich, Maria, Lynn, Teresa and Tounsi, Lamia (2016) Is all that glitters in MT quality estimation really gold standard? In: 26th International Conference on Computational Linguistics, 11-17 Dec 2016, Osaka, Japan. ISBN 978-4-87974-702-0 (2016) Abstract: Human-targeted metrics provide a compromise between human evaluation of machine translation, where high inter-annotator agreement is difficult to achieve, and fully automatic metrics, such as BLEU or TER, that lack the validity of human assessment. Human-targeted translation edit rate (HTER) is by far the most widely employed human-targeted metric in machine translation, commonly employed, for example, as a gold standard in evaluation of quality estimation. Original experiments justifying the design of HTER, as opposed to other possible formulations, were limited to a small sample of translations and a single language pair, however, and this motivates our re-evaluation of a range of human-targeted metrics on a substantially larger scale. Results show significantly stronger correlation with human judgment for HBLEU over HTER for two of the nine language pairs we include and no significant difference between correlations achieved by HTER and HBLEU for the remaining language pairs. Finally, we evaluate a range of quality estimation systems employing HTER and direct assessment (DA) of translation adequacy as gold labels, resulting in a divergence in system rankings, and propose employment of DA for future quality estimation evaluations. Keyword: Machine translating URL: http://doras.dcu.ie/23608/ BASE Hide details

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