[PDF] Top 20 Forced Derivation Tree based Model Training to Statistical Machine Translation

... Following the common practice in SMT research, the MERT algorithm (Och, 2003) is used to tune fea- ture weights in MRM. Due to the fact that all FDTs of each sentence pair share identical translation, we cannot ... See full document

... to model ambiguities in representing the source language with lattices and were able to re- port improvements over their respective ...is based on a single, comprehensive probabilis- tic method, like a ... See full document

... Phrase-based models can robustly perform trans- lations that are localized to substrings that are com- mon enough to have been observed in training. But Koehn et al. (2003) find that phrases longer than ... See full document

... Nowadays statistical machine translation shows its benefits and has received much ...phrase-based statistical machine translation was carefully ...Markov Model(HMM) ... See full document

... (E-J) translation. Table 2 shows the training, de- velopment and test corpus ...phrase-based translation model training, we used the GIZA++ toolkit (Och and Ney, 2003), and ... See full document

... string-to-tree statistical machine translation based on the selectional association measure of Resnik ...guage model (RDLM) (Sennrich, 2015) and find that neither of the features ... See full document

... HPSG tree/forest, each leaf node generally introduces a predicate, which is represented by the pair of LEXENTRY (lexical entry) feature and PRED (predicate type) ...fast tree-to-string ...the tree ... See full document

... phrase- based system without adding heavy computational complexity to the ...abstraction tree that is a shallow and nested representation, ...dependency tree as ...sentence based on a ... See full document

... generative model for map- ping natural language sentence to ...this model finds the Viterbi λ-hybrid trees for all training instances, based on the learned pa- rameters of the generative ... See full document

... our model is that TATs can be automatically acquired to capture linguistically motivated reordering at both low (word) and high (phrase, clause) ...the training of TAT-based model is less ... See full document

... Rate Training (MERT) is an effective means to estimate the feature func- tion weights of a linear model such that an automated evaluation criterion for measuring system performance can directly be optimized ... See full document

... of training phrase segmentation model for phrase- based statistical machine ...segmentation based on the translation ...iterative training algorithm of the ... See full document

... of machine translation is greatly improved by applying neural networks par- tially in a Statistical Machine Translation (SMT) pipeline (Zou et ...or training a end-to-end neural ... See full document

... suggested translation (Simard and Isa- belle, ...a Translation-Services Provider (TSP) company to reliably determine in advance the increase in translator productivity due to the use of MT and to adjust ... See full document

... The training data, as same as Cui et ...SMT model similar to Chiang (2005). The trigram target language model is trained from the Xinhua portion of English Gi- gaword corpus (Graff and Cieri, ...for ... See full document

... ficiently model several syntactic features, includ- ing long-distance ...Regular Tree Languages (RTLs), which can represent Context-free Languages (CFLs) since a set of all syntactic trees of a CFL is an ... See full document

... in statistical machine translation (SMT) mostly settles itself in the domain of either phrase-based or ...phrase translation. However, it is hard for phrase-based models to learn ... See full document

... phrasal translation and equips itself with a maximum entropy based reordering model (Xiong et ...bilingual training data which consists of ...the training data in two directions and ... See full document

... the training data and then automatically extracted the rewriting pat- ...syntactic tree of the source language ...entropy model is developed to determine how probable the children of a node are to be ... See full document

... models based on PCFGs can be learned from source-parsed bitext and then applied in the preprocessing ...the translation unit from phrases to tree-to-string align- ment templates (TATs) while we do ... See full document