[PDF] Top 20 Exploiting Pre Ordering for Neural Machine Translation
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Exploiting Pre Ordering for Neural Machine Translation
... Neural Machine Translation (NMT) has drawn much attention due to its promising translation performance in recent ...during translation are more likely to be ...the ... See full document
7
Improving Back Translation with Uncertainty based Confidence Estimation
... in exploiting abundant monolingual cor- pora to improve low-resource neural machine translation (NMT), the synthetic bilingual cor- pora generated by NMT models trained on limited authentic ... See full document
12
Exploiting Linguistic Resources for Neural Machine Translation Using Multi task Learning
... many neural MT sys- tems is that they do not translate parts of the source sentence, or that parts of the source sentence are translated ...the translation that ex- actly matches the reference the ... See full document
10
Incorporating Word and Subword Units in Unsupervised Machine Translation Using Language Model Rescoring
... unsupervised machine translation track of the WMT’19 news shared task from German to ...tistical machine translation (PBSMT) model and a pre-trained language model to combine word-level ... See full document
8
System Description: Dependency based Pre ordering for Japanese Chinese Machine Translation
... dependency-based pre-ordering ...of pre-ordering: 1) global pre-ordering reorders the cases directly depending on the verb of “bunmatu” case; 2) local pre-ordering ... See full document
5
Dependency-based Pre-ordering For English-Vietnamese Statistical Machine Translation
... In addition, we focus on analyzing some popular structures of English language when translating to Vietnamese language. This analysis can achieve remarkable improvements in translation performance. Because English ... See full document
14
Two Stage Pre ordering for Japanese to English Statistical Machine Translation
... Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexandra Constantin, and Evan ... See full document
5
Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks
... Semantic representations have long been ar- gued as potentially useful for enforcing mean- ing preservation and improving generalization performance of machine translation methods. In this work, we are the ... See full document
7
Chinese to Japanese Patent Machine Translation based on Syntactic Pre ordering for WAT 2016
... patent machine translation is the complex syntactic structure of patent documents, which typically have long sentences that complicate MT reordering, especially for word order in distant ...patent ... See full document
5
Exploiting Multilingualism through Multistage Fine Tuning for Low Resource Neural Machine Translation
... This paper focuses on (a) improving the per- formance of NMT for translating English to low- resource languages (b) via exploiting multilingual- ism (c) through transfer learning based on multi- stage fine-tuning. ... See full document
7
Hungarian translators’ perceptions of Neural Machine Translation in the European Commission
... offers translation services to other Commission Directorates-General, who send translation requests to a central DGT service that pre-processes texts automatically using various ...this ... See full document
7
When and Why Are Pre Trained Word Embeddings Useful for Neural Machine Translation?
... why pre- trained embeddings may be effective in NMT, par- ticularly in low-resource scenarios: (1) there is a sweet-spot where word embeddings are most ef- fective, where there is very little training data but not ... See full document
7
Equalizing Gender Bias in Neural Machine Translation with Word Embeddings Techniques
... this translation contains gender bias since it ig- nores the fact that, for both cases, “friend” is a female and translates by focusing on the occupa- tional stereotypes, ... See full document
8
Global Pre ordering for Improving Sublanguage Translation
... statistical machine translation (SMT) which uses a syntactic parser to extract the global sentence struc- ture, or the skeleton, from syntactic trees and uses conventional SMT to train global reordering ... See full document
10
Recycling a Pre trained BERT Encoder for Neural Machine Translation
... In this paper, an NMT system that incorporates a BERT encoder was presented. We applied two- stage optimization, that is, decoder training and fine-tuning, because the number of unlearned pa- rameters was as large as the ... See full document
9
Exploiting Source side Monolingual Data in Neural Machine Translation
... the translation quality can be further improved (Lines 7-10 in Table ...improve neural machine translation and our multi-task learning is more ... See full document
11
Exploiting Deep Representations for Neural Machine Translation
... Deep representations have proven to be of pro- found value in machine translation (Meng et al., 2016; Zhou et al., 2016). Multiple-layer encoder and decoder are employed to perform the transla- tion task ... See full document
10
Exploiting Monolingual Data at Scale for Neural Machine Translation
... will output one translation by either beam search or random sampling according to the model out- put distribution. Random sampling explores more possibility for the unknown generated sentence, which may benefit ... See full document
10
Supertag Based Pre ordering in Machine Translation
... Our objective is to reduce the structural di- vergence by reordering words in the source language (English) to conform to the target language (Hindi) word order and then provide this data to train a pharse based SMT ... See full document
9
Pre Translation for Neural Machine Translation
... of neural and phrase-based machine translation ...The pre-translation framework provides a straightforward way to support such ...final translation using an NMT ...the ... See full document
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