[PDF] Top 20 Findings of the 2011 Workshop on Statistical Machine Translation
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Findings of the 2011 Workshop on Statistical Machine Translation
... crowdsourcing translation efforts, the Microsoft Translator team de- veloped a Haitian Creole statistical machine transla- tion engine from scratch in a compressed timeframe (Lewis, ...volunteers, ... See full document
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Findings of the 2009 Workshop on Statistical Machine Translation
... Table 7 shows the correlation of automatic met- rics when they rank systems that are translating into English. Note that TERp, TER and wcd6p4er are error metrics, so a negative correlation is bet- ter for them. The ... See full document
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Findings of the 2012 Workshop on Statistical Machine Translation
... UEDIN (R, S): The system uses the baseline fea- tures along with some additional features: bi- nary features for named entities in source using Stanford NER Tagger; binary indicators for oc- currence of quotes or ... See full document
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Findings of the 2010 Joint Workshop on Statistical Machine Translation and Metrics for Machine Translation
... The method employed to collect human judgments of rank preferences at the segment level produces a sparse matrix of decision points. It is unclear whether attempts to normalize the segment level rankings to 0.0–1.0 ... See full document
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Findings of the 2013 Workshop on Statistical Machine Translation
... LORIA (T1.1): The system uses the 17 baseline features, plus several numerical and boolean features computed from the source and target sentences (Langlois et al., 2012). These are based on language model information ... See full document
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Findings of the 2014 Workshop on Statistical Machine Translation
... referential translation machines (RTM) (Bic¸ici, 2013) and parallel feature decay algorithms (ParFDA5) (Bic¸ici et ...WMT14 translation task and the language model cor- pora provided by LDC for English and ... See full document
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Findings of the 2015 Workshop on Statistical Machine Translation
... Regarding the approaches proposed, this first experience was a conservative but, at the same time, promising first step. Although participants performed the task sharing the same statistical ap- proach to APE, the ... See full document
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Findings of the Second Workshop on Neural Machine Translation and Generation
... using the C++-decoder decoder for OpenNMT. 5 . The second trend was the use of data augmenta- tion techniques allowing the systems to train on data other than the true references. Teams Amun, Marian, and OpenNMT all ... See full document
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The UA Prompsit hybrid machine translation system for the 2014 Workshop on Statistical Machine Translation
... factored translation models do (Koehn and Hoang, 2007; Graham and van Genabith, ...independent statistical models for the translation of the different factors (lemmas, lexi- cal categories, ... See full document
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The University of Maryland Statistical Machine Translation System for the Fifth Workshop on Machine Translation
... comes increasingly glaring, as the remote SRILM memory footprint drops to ≈450MB, a factor of nearly 24 compared to the local SRILM and a fac- tor of 10 compared to the process size with the RandLM. Thus, using the ... See full document
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The University of Maryland Statistical Machine Translation System for the Fourth Workshop on Machine Translation
... Both German and Hungarian have a large number of compound words that are created by concate- nating several morphemes to form a single ortho- graphic token. To deal with productive compound- ing, we employ word ... See full document
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Omnifluent English to French and Russian to English Systems for the 2013 Workshop on Statistical Machine Translation
... probabilistic translation models, including phrase- based and word-based lexicons, as well as reorder- ing models and target n-gram language ...a translation of the whole ...the translation process. ... See full document
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Proceedings of the 1st Workshop on Semantics Driven Statistical Machine Translation (S2MT 2015)
... decades, statistical machine translation (SMT) has made a substantial progress from word-based to phrase and syntax-based ...where translation quality increases more slowly even if we use ... See full document
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Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
... Samuel Larkin, Boxing Chen, George Foster, Ulrich Germann, Eric Joanis, Howard Johnson and Roland Kuhn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... See full document
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Continuous Measurement Scales in Human Evaluation of Machine Translation
... nual Workshop on Statistical Machine Translation (WMT) use human judgments of translation qual- ity to produce official rankings in shared tasks, ini- tially using an two-item ... See full document
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ParFDA for Fast Deployment of Accurate Statistical Machine Translation Systems, Benchmarks, and Statistics
... Moses statistical machine translation (SMT) sys- tems for all language pairs in the workshop on statistical machine translation (Bojar et ...(WMT15) translation ... See full document
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Proceedings of the Ninth Workshop on Statistical Machine Translation
... the workshop, in addition to soliciting relevant papers for review and possible presentation, we conducted four shared tasks: a general translation task, a medical translation task, a quality ... See full document
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Proceedings of the Eighth Workshop on Statistical Machine Translation
... our workshop was to use parallel corpora for machine ...this workshop we encouraged researchers to investigate ways to improve the performance of SMT systems for diverse languages, including ... See full document
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Proceedings of the Seventh Workshop on Statistical Machine Translation
... the workshop, in addition to soliciting relevant papers for review and possible presentation, we conducted three shared tasks: a translation task, a quality estimation task, and a task to test automatic ... See full document
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Proceedings of the Tenth Workshop on Statistical Machine Translation
... Santanu Pal, Mihaela Vela, Sudip Kumar Naskar and Josef van Genabith . . . . . . . . . . . . . . . . . . . . 216 Why Predicting Post-Edition is so Hard? Failure Analysis of LIMSI Submission to the APE Shared Task ... See full document
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