[PDF] Top 20 A Neural Reordering Model for Phrase based Translation

... machine translation system and neu- ral classifier are trained separately, the neural network training only has an indirect effect on translation ...machine translation system and ... See full document

... noisy phrase pairs in the phrase ...a phrase vector by simply embedding word vectors of the source and target language phrases and did not consider the adequacy of the translation between the ... See full document

... First, our cohesion penalty is by nature more tol- erant to some meaningful noncontituent translations. For example, constituency constraints in (Chiang, 2005; Marton and Resnik, 2008; Chiang et al., 2009) would penalize ... See full document

... different translation systems in terms of translation quality ...calized reordering model improves the translation quality of ...in phrase-based trans- lation ...the ... See full document

... for phrase- based ...dress reordering, which is often considered a weak point of phrase-based ...hierarchical reordering model as our base- line, we show that simple ... See full document

... demanding reordering task of translating between two distant languages, En- glish and ...described translation direction: English to ...the reordering challenges of this translation ... See full document

... improve translation output– has been explored by many ...for translation from French to English, where context-free constituency reordering rules are acquired automatically using source and target ... See full document

... language model, although his model does not beat a supertag factored PMT ...improve translation, augment- ing SCFG rules by consulting the multiple deriva- tions in the parse chart of Clark and ... See full document

... In Table 3 and Table 4, we show the trans- lation results for the BTEC task. First, we observe that the overall quality is rather high on this task. The average length of the used alignment templates is about five source ... See full document

... hierarchical phrase-based translation (Chiang, 2007), a weighted synchronous context-free gram- mar is induced from parallel ...are: phrase translation probabilities and lexical ... See full document

... a phrase-based decoder, which includes the following models: an n-gram target- side language model (LM), a phrase translation model and a word-based lexicon ...use ... See full document

... traditional phrase-based features: distortion and lexicalized re- ordering into Hiero as ...the translation quality of CKY Hiero with the full rule ...the translation for non- terminal ... See full document

... Hierarchical phrase-based translation (Chiang, 2005; Chiang, 2007) extends the highly lexicalized models from phrase-based translation systems in order to model ... See full document

... combine phrase- based features and tree-based features into one ...better translation for Chinese-English transla- ...the model can in- clude complete rule sets together with word ... See full document

... of reordering, the experiments takes 500 authentic patent texts provide by SIPO as the training ...Machine Translation Pilot Task, containing 2,000 bilingual Chinese-English sentence ... See full document

... initial phrase pair to the maximum coverage of 10 source words, we will lose the collocations such as “de” and “jvqing”, which indicates a reordering, by only considering the non-linguistic ...and ... See full document

... global reordering model that explicitly models long distance re- ordering 1 ...of reordering patterns, namely MA (monotone adjacent), MG (monotone gap), RA (reverse adjacent), and RG (reverse ...are ... See full document

... leave translation results out of this ...on translation quality, including phrase extraction, minimum error training and additional parameter settings of the ... See full document

... of phrase-based SMT is that phrase cohere across two languages (Fox, 2002), which means phrases in one language tend to be moved together during ...the reordering exam- ples extracted by the ... See full document

... To train B, we used binary feature functions ϕ as used in (Tromble and Eisner, 2009), which were introduced for dependency parsing by Mc- Donald et al. (2005). Table 2 shows the kind of features we used in our ... See full document