[PDF] Top 20 Exploiting Monolingual Data at Scale for Neural Machine Translation
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Exploiting Monolingual Data at Scale for Neural Machine Translation
... of data are then merged together to get the bilingual ...clean data and 18M Paracrawl data, which are denot- ed as WMT and WMTPC respectively for ease of ...The monolingual data we use ... See full document
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Iterative Back Translation for Neural Machine Translation
... fast translation, ...the monolingual data into smaller parts and distribute these parts over different ...back translation is quite feasible with existing modern GPU ... See full document
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PARABANK: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-Constrained Neural Machine Translation
... Czech-English neural machine translation (NMT) system to generate novel paraphrases of English ref- erence ...a monolingual NMT model with the same support for lexically-constrained decoding ... See full document
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Enhancement of Encoder and Attention Using Target Monolingual Corpora in Neural Machine Translation
... encoder-decoder neural machine ...target monolingual corpora are automatically translated into source sentences, is effective in improving the decoder, but is unreliable for enhanc- ing the ...target ... See full document
9
Exploiting Source side Monolingual Data in Neural Machine Translation
... Neural Machine Translation (NMT) based on the encoder-decoder architecture has recently become a new ...target-side monolingual data can greatly enhance the decoder model of ... See full document
11
Exploiting Linguistic Knowledge for Low-Resource Neural Machine Translation
... English machine translation task, the main problem is that the source-side Turkish is a morphologically-rich language with derivational morphology ...inaccurate translation results ... See full document
9
Using Target side Monolingual Data for Neural Machine Translation through Multi task Learning
... target-side monolingual data into NMT through multi-task ...lingual data from ...parallel data, we believe there is value in pursuing this line of re- search further to simplify training ... See full document
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Exploiting Deep Representations for Neural Machine Translation
... Dataset. To compare with the results reported by previous work (Gehring et al., 2017; Vaswani et al., 2017; Hassan et al., 2018), we conducted experiments on both Chinese⇒English (Zh⇒En) and English⇒German (En⇒De) ... See full document
10
Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks
... more data is beneficial for accurately modeling in- fluence of semantics on the translation ...enough data, RNNs were able to capture syntactic dependency and thus reducing the benefits from using ... See full document
7
Context Aware Monolingual Repair for Neural Machine Translation
... only monolingual data to model inconsisten- cies between sentence-level ...document-level data is parallel, and translations are sampled from the source side of the sentences in a group rather than ... See full document
10
Dynamic Data Selection for Neural Machine Translation
... Regarding data selection for SMT, previous work has targeted two goals; to reduce model sizes and training times, or to adapt to new ...domains. Data selection methods for domain adaptation mostly employ ... See full document
11
Exploiting Out of Domain Parallel Data through Multilingual Transfer Learning for Low Resource Neural Machine Translation
... pseudo-parallel data (Sennrich et ...Pseudo-parallel data can be used to augment existing parallel corpora for train- ing, and previous work has reported that such data generated by so-called ... See full document
12
Exploiting Linguistic Resources for Neural Machine Translation Using Multi task Learning
... the translation and POS tagging task. Although the POS data is out-of-domain and significantly smaller than the parallel training data for the trans- lation task ... See full document
10
Log linear Combinations of Monolingual and Bilingual Neural Machine Translation Models for Automatic Post Editing
... of neural translation models to the APE problem and achieve good results by treating different models as components in a log-linear model, allowing for multi- ple inputs (the MT-output and the source) that ... See full document
8
Copied Monolingual Data Improves Low Resource Neural Machine Translation
... coder. Monolingual data was then introduced by adding an autoencoder ...parallel data to pre-train source → target and target→source NMT systems; they then added monolingual data to the ... See full document
9
Improving Neural Machine Translation Models with Monolingual Data
... on monolingual training data and incorporate them into the neural network through shallow or deep fusion, we propose techniques to train the main NMT model with monolingual data, ... See full document
11
Zero Resource Neural Machine Translation with Monolingual Pivot Data
... that monolingual data from a lan- guage other than the source and target languages can aid NMT performance, complementing litera- ture on using source- and target-language mono- lingual data in ... See full document
9
Using Monolingual Data in Neural Machine Translation: a Systematic Study
... To recap our answers to our initial questions: the quality of BT actually matters for NMT (cf. § 3.1) and it seems that, even though artificial source are lexically less diverse and syntactically complex than real ... See full document
12
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 ... See full document
12
Reference Bias in Monolingual Machine Translation Evaluation
... Therefore, monolingual evaluation under- mines the reliability of quality ...specific translation task, where the number of possible translations is indeed limited, the as- sessment should be performed by ... See full document
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