[PDF] Top 20 Improving Statistical Machine Translation with Monolingual Collocation

... To investigate the effectiveness of the method proposed in section 4, we only use the colloca- tion model CM-3 as described in section 5.1. The results are shown in Table 5. When the phrase collocation ... See full document

... (Brown et al. (1993) provides a more detailed deri- vation of this identity.) Although simple, this ap- proach has proven effective in SMT for several reasons. First and foremost, phrasal scoring by Model 1 avoids the ... See full document

... GIZA++ statistical alignment package is used to perform the word alignments, which are later combined into phrase alignments in the Moses pipeline (Och and Ney, 2003) to build the sentence simplification ... See full document

... We use target-side monolingual data to ex- tend the vocabulary of the translation model in statistical machine translation. This method called “reverse self-training” improves the de- ... See full document

... the translation and language models can further improve the translation ...a translation model trained on a concatenation of S → T and T → S parallel corpora and a language model compiled from a ... See full document

... only if there is some possible source of additional informa- tion in the French. If it has been produced by a method that had been shown to be superior, perhaps even involving human editing, then there is such a possible ... See full document

... to translation can- didates (Rapp, 1995; Koehn and Knight, 2002; Haghighi et ...assign translation can- didates to OOVs (Marton et ...propagate translation candidates across a graph with phrasal ... See full document

... in statistical machine trans- ...Chinese-to-English translation tasks with large-scale training data demonstrate that statistical machine translation using verbal selectional ... See full document

... Each seed could be translated by itself, indepen- dently from the fillers. However, some initial ex- periments showed that the filler text snippets help the algorithm to contextualize the translation, e.g. shot X ... See full document

... the translation result with the reference in term of BLEU score instead of F-score because of two main ...SMT translation quality in terms of BLEU score ...the translation result data based on ... See full document

... of machine translation outputs are where the authors successfully performed statistical post-editing (SPE) of rule-based machine translation ...a monolingual setting, trained on ... See full document

... phrase table itself from monolingual texts. Across all of our experiments, we use the phrase table that the bilingual model learned from the Europarl parallel corpus. We keep its phrase pairs, but we drop all of ... See full document

... a monolingual corpus of a volu- minous ...vector machine (SVM), and con- ditional random field ...on monolingual corpus, the use of a bilingual corpus as an guideline for word segmentation in ... See full document

... Reordering is of essential importance for phrase based statistical machine translation (SMT). In this paper, we would like to present a new method of reordering in phrase based SMT. We inspired from ... See full document

... for improving machine translation ...two translation tasks and with both the standard phrase-based and the hierarchi- cal phrase-based translation ...frequency translation ... See full document

... The analysis of terms assigned to error class four shows that both methods are affected by similar problems. The main source of error is the correct detection of the source term domain, which results in a translated term ... See full document

... of monolingual target data into the source language, and treating this synthetic data as additional train- ing ...domain monolingual data, back-translated into the source language, can be effectively used ... See full document

... high translation score to justify itself as an appropriate ...disfluent translation could be repaired to a fluent one ...be translation of each ... See full document

... In our experiments, the out-of-domain training cor- pus comes from the FBIS corpus and the Hansard- s part of LDC2004T07 corpus (54.6K documents with 1M parallel sentences, 25.2M Chinese words and 29M English words). We ... See full document

... compares translation output between baseline and the +tgt-FMS-rr extension, showing that the system is able to correct syntactical er- rors, but also, that some changes consist only of swapping translations for a ... See full document