[PDF] Top 20 Phrase based Machine Translation using Multiple Preordering Candidates
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Phrase based Machine Translation using Multiple Preordering Candidates
... Web using an in-house ...optimized using the development data and final evaluation is performed using the test ...performed using one-best preordered source sentences and corresponding target ... See full document
10
Japanese to English Machine Translation using Preordering and Compositional Distributed Semantics
... Many machine learning algorithms require fixed length vectors as input. Of the various differ- ent ways to map words to vectors, neural network based models have proven very effective recently. Vector ... See full document
9
A Comparison of Pivot Methods for Phrase Based Statistical Machine Translation
... translation candidates. 8 Selecting the highest scoring translation from a small pool did not always lead to better ...sentence translation strategy, we need to use a large ...slow ... See full document
8
Integrating empty category detection into preordering Machine Translation
... accurate machine translation ...into preordering-based statistical machine ...category candidates to improve the accuracy of machine ...discriminative preordering ... See full document
9
Building a Non Trivial Paraphrase Corpus Using Multiple Machine Translation Systems
... use phrase-based machine translation (PBMT) and neural machine translation (NMT) to gener- ate two different Japanese sentences from one En- glish ... See full document
7
HSSA tree structures for BTG-based preordering in machine translation
... for machine translation (MT) is the different order of the same conceptual units in the source and target ...adequate translation in the target language, the default phrase-based ... See full document
10
Source Side Classifier Preordering for Machine Translation
... most from preordering and gain more than 7 BLEU relative to the phrase-based baseline and still more than 3 BLEU for the forest-to-string system. Simi- lar improvements were reported by Xu et al. ... See full document
11
Phrase Based Evaluation for Machine Translation
... calculating phrase similarity, allocating weight to each phrase, and finding a maximum similarity ...function based on WordNet but also explore a topic similarity function based on a popular ... See full document
10
Phrase based Unsupervised Machine Translation with Compositional Phrase Embeddings
... Step 2: extract phrase candidates. Since we can not learn vectors for all phrases in the corpus, we have to decide which phrases to use to learn vectors for. One option is to randomly glue desired number of ... See full document
7
Recursive Neural Network Based Preordering for English to Japanese Machine Translation
... statistical machine translation (SMT) (Tillmann, 2004; Hayashi et ...problems, preordering (Xia and McCord, 2004; Wang et ...proposed. Preordering reorders source sentences before ... See full document
7
Phrase Based Statistical Machine Translation: A Level of Detail Approach
... all phrase translations in one step, either di- rectly from the sentence pair or through word ...of phrase translation candidates at ...maximum phrase length to reduce the choice of ... See full document
12
Clustered Word Classes for Preordering in Statistical Machine Translation
... The translation results for the English–German experiments are shown in Table ...report translation results for two metrics, Bleu (Papineni et ...performed using approxi- mate randomization (Riezler ... See full document
7
Supertagged Phrase Based Statistical Machine Translation
... In this paper we explore a novel approach towards extending a standard PBSMT system with syntactic descriptions: we inject lexical descriptions into both the target side of the phrase translation table and ... See full document
8
Bidirectional Phrase based Statistical Machine Translation
... 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 order until ... See full document
9
Phrase Based & Neural Unsupervised Machine Translation
... First, they carefully initialize the MT system with an inferred bilingual dictionary. Second, they leverage strong language models, via train- ing the sequence-to-sequence system (Sutskever et al., 2014; Bahdanau et al., ... See full document
11
Source side Preordering for Translation using Logistic Regression and Depth first Branch and Bound Search
... novel preordering approach based on a logistic regression model trained to predict whether to swap nodes in the source-side dependency ...nodes, using the regression scores to guide the ... See full document
10
Phrase Based Backoff Models for Machine Translation of Highly Inflected Languages
... Previous approaches have used morpho-syntactic knowledge mainly at the low-level stages of a ma- chine translation system, i.e. for preprocessing. (Niessen and Ney, 2001a) use morpho-syntactic knowledge for ... See full document
8
Pseudo Word for Phrase Based Machine Translation
... most Phrase-Based Statistical Machine Translation (PB-SMT) systems starts from automatically word aligned parallel corpus generated from word-based models (Brown et ...of phrase ... See full document
9
SampleRank Training for Phrase Based Machine Translation
... ses are generated by glossing. For each word in the source, the most likely translation option (according to the weighted phrase-internal score) is selected, and these translations are joined together ... See full document
11
Improvements in Phrase Based Statistical Machine Translation
... the phrase-based sys- tem, we use the following feature functions: a trigram language model, the phrase translation model and the word-based lexicon ...and phrase penalty fea- ... See full document
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