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[PDF] Top 20 Sentiment Aware Neural Machine Translation

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Sentiment Aware Neural Machine Translation

Sentiment Aware Neural Machine Translation

... existing machine trans- lation pipelines (Chan et ...overall translation performance as measured by ...improve translation quality and accuracy of am- biguous ... See full document

7

Beyond Weight Tying: Learning Joint Input Output Embeddings for Neural Machine Translation

Beyond Weight Tying: Learning Joint Input Output Embeddings for Neural Machine Translation

... Tying the weights of the target word em- beddings with the target word classifiers of neural machine translation models leads to faster training and often to better translation quality. Given ... See full document

11

Improved Neural Machine Translation with a Syntax Aware Encoder and Decoder

Improved Neural Machine Translation with a Syntax Aware Encoder and Decoder

... We also extend the decoder to incorporate infor- mation about the source syntax into the attention model. We have observed two issues in transla- tions produced using the tree encoder. First, a syn- tactic phrase in the ... See full document

10

A Simple and Effective Approach to Coverage Aware Neural Machine Translation

A Simple and Effective Approach to Coverage Aware Neural Machine Translation

... Another interesting question is whether the N- MT systems can generate translations with ap- propriate lengths. To seek its answer, we stud- ied the length difference between the MT output and the shortest reference. ... See full document

6

Syntax Enhanced Neural Machine Translation with Syntax Aware Word Representations

Syntax Enhanced Neural Machine Translation with Syntax Aware Word Representations

... There have been several studies for NMT us- ing dependency syntax. Hashimoto and Tsuruoka (2017) propose to combine the head information with sequential words together as source encoder inputs, where their input trees ... See full document

11

Context Aware Neural Machine Translation Learns Anaphora Resolution

Context Aware Neural Machine Translation Learns Anaphora Resolution

... proxy translation, can be achieved by incorporating specialized features in the attention ...pronoun translation. Future work could also investigate whether context-aware NMT systems learn other ... See full document

11

Unsupervised Domain Adaptation for Neural Machine Translation with Domain Aware Feature Embeddings

Unsupervised Domain Adaptation for Neural Machine Translation with Domain Aware Feature Embeddings

... Baselines. We compare our methods with two baseline models: 1) The copied monolingual data model (Currey et al., 2017) which copies tar- get in-domain monolingual data to the source side; 2) Back-translation ... See full document

6

Morphology aware Word Segmentation in Dialectal Arabic Adaptation of Neural Machine Translation

Morphology aware Word Segmentation in Dialectal Arabic Adaptation of Neural Machine Translation

... chine translation (MT) models for dialectal Arabic (DA) are rather ...morphology- aware DA word segmentation to other word segmentation approaches like Byte Pair En- coding (BPE) and Sub-word Regularization ... See full document

7

A Large Scale Test Set for the Evaluation of Context Aware Pronoun Translation in Neural Machine Translation

A Large Scale Test Set for the Evaluation of Context Aware Pronoun Translation in Neural Machine Translation

... The simplest possible extension is to trans- late units larger than sentences. Tiedemann and Scherrer (2017) concatenate each sentence with the sentence that precedes it, for the source side of the corpus or both sides. ... See full document

12

Graph Convolutional Encoders for Syntax aware Neural Machine Translation

Graph Convolutional Encoders for Syntax aware Neural Machine Translation

... into neural attention-based encoder- decoder models for machine ...of neural networks developed for modeling graph-structured ...English-Czech translation experiments for different types of ... See full document

11

Context Aware Smoothing for Neural Machine Translation

Context Aware Smoothing for Neural Machine Translation

... discrete translation lexicons into NMT to imrpove the translations of these low-frequency ...the translation of OOV itself and ignored the other negative effect caused by the OOV, such as the translations ... See full document

10

Context Aware Monolingual Repair for Neural Machine Translation

Context Aware Monolingual Repair for Neural Machine Translation

... Modern sentence-level NMT systems often produce plausible translations of isolated sen- tences. However, when put in context, these translations may end up being inconsistent with each other. We propose a monolingual ... See full document

10

A Character Aware Encoder for Neural Machine Translation

A Character Aware Encoder for Neural Machine Translation

... character-aware neural machine translation (NMT) model that views the input sequences as sequences of characters rather than ...Chinese-English translation tasks show that the proposed ... See full document

8

Context Aware Neural Machine Translation Decoding

Context Aware Neural Machine Translation Decoding

... general translation quality, allowing to rank them as ...the translation from the fused sys- tem is better than the baseline, and they consider the quality of both translations to tie 19% of the ... See full document

11

Selective Attention for Context aware Neural Machine Translation

Selective Attention for Context aware Neural Machine Translation

... but it is still almost 40% faster than Miculicich et al. (2018). At decoding time, our Hierarchical Attention model is almost equivalent to Miculicich et al. (2018) and only 13% slower than Zhang et al. (2018). Hence, ... See full document

11

Data augmentation using back translation for context aware neural machine translation

Data augmentation using back translation for context aware neural machine translation

... Although we have used simple beam search with the beam size of 5 for back-translation, those randomized back-translation strategies, if adopted, should strongly boost our baseline (sentence-level ... See full document

10

Context aware Neural Machine Translation with Coreference Information

Context aware Neural Machine Translation with Coreference Information

... Our proposed model can encode not only the sen- tence to be translated but also its preceding and succeeding sentences together, based on the re- sults of coreference resolution. Therefore, infor- mation about sentence ... See full document

6

Boosting Neural Machine Translation

Boosting Neural Machine Translation

... The method we proposed focuses on training process only. There is no restriction for the neural network structure. It can be used in any data paral- lelism framework and then distributed onto multi- GPUs. Also, ... See full document

6

Iterative Back Translation for Neural Machine Translation

Iterative Back Translation for Neural Machine Translation

... Farsi translation is much more difficult than French; or a result of the diverse mix of domains in the parallel training data (news with LDC and technical talks with TED) where the domain in monolingual data is ... See full document

7

Generalizing Back Translation in Neural Machine Translation

Generalizing Back Translation in Neural Machine Translation

... English translation task, which allows us to directly compare the properties of synthetic and natural ...of translation quality, these do not result in consistent improvements over the typical beam search ... See full document

8

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