[PDF] Top 20 Decoder based Discriminative Training of Phrase Segmentation for Statistical Machine Translation

... proposed phrase segment boundary labeling in phrase- based ...the decoder is perfectly aware of the segment boundary information of input ...base decoder and the reference ... See full document

... standard phrase extraction procedure in SMT consists of two phases: (i) word-alignment training ...heuristic phrase extraction and relative frequency based phrase trans- lation ... See full document

... novel segmentation approach for Phrase-Based Statistical Machine Translation (PB-SMT) to languages where word boundaries are not obviously marked by using both monolingual and ... See full document

... The goal of the training algorithm is to learn the feature weights from the word aligned corpus. For word-alignment, we used the IBM Model 5 imple- mented in GIZA++ along with the growing heuris- tics (Koehn et ... See full document

... One benefit of segmented translation is the ability to generate new compounds and inflections, that were not seen in the training data. However, the ability can also lead to errors, e.g when an English word ... See full document

... Statistical machine translation systems are normally optimised for a chosen gain func- tion (metric) by using MERT to find the best model ...for discriminative training of ... See full document

... In the following sections, we will present results on three tasks: Verbmobil, Xerox and Canadian Hansards. There- fore, we will show the corpus statistics for each of these tasks in this section. The training ... See full document

... continuous phrase pair (je ...2.2 Training: Lexicalized Reordering Table Phrasal-Hiero needs a phrase-based lexicalized re- ordering table to calculate the ...uous phrase-based ... See full document

... a phrase-based SMT decoder, the word se- quence of the target language is typically gener- ated in order in a forward ...the translation are generated first, then the subsequent words, in ... See full document

... Outperforming a PBSMT system on small amounts of training data is less impressive than doing so on really large sets. The issue here is scalability as well as whether the PBSMT system is able to bridge the ... See full document

... As specific MT method, we use the alignment tem- plate approach (Och et al., 1999). The key elements of this approach are the alignment templates, which are pairs of source and target language phrases to- gether with an ... See full document

... tal decoder was significantly faster than the beam search in re-decoding mode almost by a factor of 9 in the best case (for ...partial decoder states without having to re-generate hypotheses through the ... See full document

... the phrase level, these models typically have a simple distortion model that reorders phrases in- dependently of their content (Och and Ney, 2004; Koehn et ... See full document

... hierarchical phrase based ...for discriminative tuning of weights for the new ...hierarchical phrase-based SMT systems on two datasets for German-to-English ...existing phrase- ... See full document

... Evaluation exercises indicate that approximate search algorithms work well in practice (Bojar et al., 2013). The most popular algorithms pro- vide solutions with unbounded error, thus pre- cisely quantifying their ... See full document

... the ITG reorderings, we see that the ITG system always outperforms the unconstrained system. The improvement on the whole test set is statistically significant at the 95% level. 1 In Table 5 and Table 6, we show the re- ... See full document

... entropy based method for TM (Ling et ...NNLM based sentence adaptation, (Sennrich, 2012) for TM weights combination, and (Bisazza et ...indicate training all models using corresponding corpora, ... See full document

... Evaluation exercises indicate that approximate search algorithms work well in practice (Bojar et al., 2013). The most popular algorithms pro- vide solutions with unbounded error, thus pre- cisely quantifying their ... See full document

... phrasal decoder with ITG con- straints, while a number of researchers have em- ployed syntax-driven source reordering before de- coding begins (Xia and McCord, 2004; Collins et ...the decoder, not as a ... See full document

... The document-level models included in Docent include a length parity model, a semantic lan- guage model as well as a collection of document- level readability models. The length parity model is a proof-of-concept model ... See full document