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[PDF] Top 20 Exploiting Cross Sentence Context for Neural Machine Translation

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Exploiting Cross Sentence Context for Neural Machine Translation

Exploiting Cross Sentence Context for Neural Machine Translation

... In translation, considering the document as a whole can help to resolve ambiguities and ...a cross-sentence context-aware ap- proach and investigate the influence of his- torical contextual ... See full document

6

Exploiting Source side Monolingual Data in Neural Machine Translation

Exploiting Source side Monolingual Data in Neural Machine Translation

... Neural Machine Translation (NMT) based on the encoder-decoder architecture has recently become a new ...the translation and the reordered source-side monolingual sentences ... See full document

11

Sentence Level Adaptation for Low Resource Neural Machine Translation

Sentence Level Adaptation for Low Resource Neural Machine Translation

... Li et al. (2016) present a dynamic NMT ap- proach where the general NMT model is adapted per-sentence; however, they adapt on only a single similar sentence and employ their system in a high- resource ... See full document

9

Dynamic Sentence Sampling for Efficient Training of Neural Machine Translation

Dynamic Sentence Sampling for Efficient Training of Neural Machine Translation

... the sentence length and word ...static sentence-selection method for domain adaptation using the internal sentence embedding of ...a sentence weighting method with dynamic weight adjustment ... See full document

7

Exploiting Sentence and Context Representations in Deep Neural Models for Spoken Language Understanding

Exploiting Sentence and Context Representations in Deep Neural Models for Spoken Language Understanding

... sequence neural networks have been widely explored for spoken language ...Recurrent Neural Networks have been pro- posed in (Yao et ...Deep Neural Networks consisting of a composition of Restricted ... See full document

10

Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks

Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks

... of machine translation ...into neural machine transla- ...into sentence encoders and achieve improvements in BLEU scores over the linguistic-agnostic and syntax- aware versions on the ... See full document

7

Exploiting Linguistic Knowledge for Low-Resource Neural Machine Translation

Exploiting Linguistic Knowledge for Low-Resource Neural Machine Translation

... In this paper, we propose a multi-source NMT approach for the low-resource NMT to explicitly utilize the source-side linguistic knowledge, which models the word sequence in parallel to the linguistic features by using ... See full document

9

SHEF LIUM NN: Sentence level Quality Estimation with Neural Network Features

SHEF LIUM NN: Sentence level Quality Estimation with Neural Network Features

... extract sentence embeddings and cross-entropy scores, (ii) a neural net- work machine translation (NMT) model, (iii) a set of QuEst features, and (iv) a com- bination of features ... See full document

5

Context Aware Neural Machine Translation Decoding

Context Aware Neural Machine Translation Decoding

... As future work, we find interesting to pursue an in-depth manual evaluation to analyze how end users perceive the variations produced by our sys- tems. The next step will be to test this imple- mentation within ... See full document

11

Context Aware Smoothing for Neural Machine Translation

Context Aware Smoothing for Neural Machine Translation

... novel context- aware smoothing method to dynamically learn a Context-Aware Representation (CAR) for each word (including OOV words) depending on its local context words in a ...a sentence, ... See full document

10

Learning Joint Multilingual Sentence Representations with Neural Machine Translation

Learning Joint Multilingual Sentence Representations with Neural Machine Translation

... The use of multiple encoders and decoders was first studied in the context of neural MT. Dong et al. (2015) used multiple decoders, i.e. 1:N training, to achieve improved NMT performance. Zoph and Knight ... See full document

11

Document Context Neural Machine Translation with Memory Networks

Document Context Neural Machine Translation with Memory Networks

... document-level neural ma- chine translation model which takes both source and target document context into account using memory ...a neural translation model equipped with two memory ... See full document

10

Improving Back Translation with Uncertainty based Confidence Estimation

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

Context aware Neural Machine Translation with Coreference Information

Context aware Neural Machine Translation with Coreference Information

... source sentence to be translated, by constructing an encoder that is based on explicit coreference ...improve translation quality when a source text has many ... See full document

6

Document Level Information as Side Constraints for Improved Neural Patent Translation

Document Level Information as Side Constraints for Improved Neural Patent Translation

... and neural translation models for patent ...or sentence-attached ...phrase-based machine translation, our features based on annotation overlap between test documents and phrase ... See full document

12

Selective Attention for Context aware Neural Machine Translation

Selective Attention for Context aware Neural Machine Translation

... document- context on both source and target-side using mem- ory networks (Maruf and Haffari, ...previous context to use and there has been no comparison between the online and offline setting except using ... See full document

11

Self Attentive Residual Decoder for Neural Machine Translation

Self Attentive Residual Decoder for Neural Machine Translation

... the context depends on the current prediction is ap- pealing, because it can be interpreted as learning internal dependencies among ...whole sentence which are easier to learn and ... See full document

14

Context Aware Monolingual Repair for Neural Machine Translation

Context Aware Monolingual Repair for Neural Machine Translation

... of translation pairs containing approx- imately 15000 4 source ...training context-aware models, for early stopping we use both convergence in BLEU score on the general development set and scores on the ... See full document

10

Exploiting Pre Ordering for Neural Machine Translation

Exploiting Pre Ordering for Neural Machine Translation

... during translation are more likely to be ignored by the NMT model, we propose to exploit the pre-ordering approach which is commonly used in Statistical Machine Transla- tion ...source sentence ... See full document

7

Exploiting Sentential Context for Neural Machine Translation

Exploiting Sentential Context for Neural Machine Translation

... We conducted experiments on WMT14 En⇒De and En ⇒ Fr benchmarks, which contain 4.5M and 35.5M sentence pairs respectively. We re- ported experimental results with case-sensitive 4- gram BLEU score. We used ... See full document

7

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