... the out-of-domain translation mod-el for domain-specific translation task. In detail, webuild an adapted translation model in the followingsteps:• Build a topic-specific translation model toquantify ... machine translation. Machine Translation, pages 187-207.Nicola Ueffing, Gholamreza Haffari and Anoop Sarkar.2008. Semi-supervised Model Adaptation for Statisti-cal Machine Translation. Machine Translation, ... ourwork has the following differences.• We focus on how to adapt a translation mod-el for domain-specific translation task with thehelp of additional in-domain monolingual cor-pora, which are...
... probability of the translation "in order to avoid" is higher than that of the translation "can we avoid". Thus, our method selects the former as the translation. Although ... Speech Translation Evalua-tion. In Processings of the International Workshop on Spoken Language Translation 2005. Philipp Koehn, Franz J. Och, and Daniel Marcu. 2003. Statistical Phrase-based Translation. ... me-thods. From the results in Table 5, it can be seen that the quality of translation is future improved. As compared with the baseline system, an abso-lute improvement of 2.40 BLEU score is...
... training phrase-based translation models, which can be used directlyin translation tasks or combined with base-line models. Experimental results on Chinese-English machine translation tasks show ... Baseline system, GS: System trained with only gen-erated sentence pairs, IT: Interpolated phrase table with GS and BL,. GA and IA are GS and IT systems trained with baseline word alignment models ... inter-polating the phrase table with the baseline phrase ta-ble, we observed improvement on Chinese-Englishmachine translation tasks and the performance iscomparable to system trained with larger manuallycollected...
... Sharon))”hf1NP0,3“(Bush) ⊔ (with (Sharon))”NPB0,1“Bush”B`ush´ıhf0CC1,2 with yˇuVP1,5“held Sharon))”PP1,3 with (Sharon)”P1,2 with NPB2,3“Sharon”Sh¯al´ongVPB3,5“held ... Faster decoding with integrated language mod-els. In Proceedings of ACL, pages 144–151, June.Liang Huang, Kevin Knight, and Aravind Joshi. 2006.Statistical syntax-directed translationwith extendeddomain ... algorithm of Miet al. (2008) to convert Fcinto a translation for-est, each hyperedge of which is associated with aconstituency to dependency translation rule. How-ever, pattern-matching failure2at...
... formachine translation evaluation. In Proceedings ofEMNLP 2004, pages 388–395, Barcelona, Spain, July.Arne Mauser, Saˇsa Hasan, and Hermann Ney. 2009. Ex-tending statistical machine translationwith ... We evaluatethe effectiveness of both models on Chinese-to-English translation tasks with large-scale trainingdata. Compared with the baseline which only usesthe forward language model, our ... dependency languagemodel to improve translation quality. To some ex-tent, these syntactically-informed language modelsare consistent with syntax-based translation modelsin capturing long-distance...
... translation performance. 6 Translation as a Search Problem The problem of finding the translation of a sen- tence can be viewed as a search problem for a path withminimal cost in a tree. If ... contain words with similar syntactic/semantic properties. To arrive at WCs having both (method COMB), we determine TL WCs with the first method and afterwards we determine SL WCs with the sec- ... model, the rule probabilities and the translation probabilities. In the search tree every node represents a partial translation for the first words or a full translation. The leaves of the tree...
... “Mandolin” is a well-known musical instrument with metal strings (usually eight) arranged in pairs, and a curved back, played with a plectrum. So its translation can be: Đàn Măng đô lin (đàn tám ... gà) 4.1.6 Translating by using a paraphrase Translation by paraphrasing is another of the possible ways in coping with problematic items in translation. When using it the translator has two ... Translating by a more general word Translation by generalisation is one of the most commonly applied strategies in dealing with various kinds of problems in translation. The translator usually...
... over phrase-pair spans, with each cell filled with multiple lin-guistically motivated labels, is coupled with the HR-SCFG design to arrive at a rich synchronous gram-mar with millions of structural ... latentrecursive structures targeting translation, we achievesignificant improvements in translation quality for 4different language pairs in comparison with a stronghierarchical translation baseline.Our ... the baseline at the 95% confidence level are labelled with a single star, at the 99% level with two. with a 3-gram language model smoothed with modi-fied Knesser-Ney discounting (Chen and Goodman,1998),...
... machine translation. In Proceedings ofACL, pages 160–167, Sapporo, Japan.Karolina Owczarzak, Josef van Genabith, and AndyWay. 2008. Evaluating machine translation with LFG dependencies. Machine Translation, ... University{mgalley,jurafsky,manning}@stanford.eduAbstractExisting evaluation metrics for machine translation lack crucial robustness: their correlations with hu-man quality judgments vary considerably across lan-guages ... main reasonis their inability to properly capture meaning: A good translation candidate means the same thing as thereference translation, regardless of formulation. Wepropose a metric that evaluates...
... encoded in the translation tables has neverbeen assessed intrinsically. To do so, we com-pare translation probabilities with concept vectorbased semantic relatedness measures with respectto ... through word translation probabil-ities. In this study, we use the correlation with human rankings for reference word pairs to inves-tigate how word translation probabilities compare with traditional ... word-to-word translation probabilities are used for rankingword-pairs with respect to their semantic related-ness.3 Parallel DatasetsIn order to obtain parallel training data for thetranslation...