[PDF] Top 20 Exploiting Source side Monolingual Data in Neural Machine Translation
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Exploiting Source side Monolingual Data in Neural Machine Translation
... just source-side monolingual corpora rather than the synthetic par- allel ...age source-side monolingual data in NMT using a simple autoencoder and skip-thought ... See full document
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Improving Neural Machine Translation Models with Monolingual Data
... Neural Machine Translation (NMT) has obtained state-of-the art performance for several language pairs, while only us- ing parallel data for ...Target- side monolingual ... See full document
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Using Monolingual Data in Neural Machine Translation: a Systematic Study
... Neural Machine Translation (MT) has radi- cally changed the way systems are ...target data, which often abounds, is used in these two ...for Neural MT devel- opers seems to be the ... See full document
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Copied Monolingual Data Improves Low Resource Neural Machine Translation
... translated data) resulted in small improvements ...more monolingual than parallel data would result in a worse performance, since the system would see true parallel data less often than copied ... See full document
9
Using Target side Monolingual Data for Neural Machine Translation through Multi task Learning
... Baselines Our baseline model consists of a 1- layer bi-directional LSTM encoder with an embed- ding size of 512 and a hidden size of 1024. The 1-layer LSTM decoder with 1024 hidden units uses an attention network with ... See full document
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Exploiting Monolingual Data at Scale for Neural Machine Translation
... target-side monolingual data has been proven to be very useful to improve neural ma- chine translation (briefly, NMT) through back translation, source-side ... See full document
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Context Aware Monolingual Repair for Neural Machine Translation
... a monolingual DocRepair model to correct inconsistencies between sentence-level ...only monolingual document-level data in the target ...a monolingual sequence-to-sequence model that maps ... See full document
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Low Resource Corpus Filtering Using Multilingual Sentence Embeddings
... open source release 6 of the Zipporah tool without ...(probabilistic translation dic- tionaries and language models) were trained on the provided clean data (excluding the dictionar- ...parallel ... See full document
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Iterative Back Translation for Neural Machine Translation
... a data-hungry approach, requiring a large amount of parallel data to reach reasonable per- formance (Koehn and Knowles, ...parallel data, ...obtain monolingual data in either the ... See full document
7
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 ... See full document
9
Exploiting Cross Sentence Context for Neural Machine Translation
... ing source and target words based on the context defined by a source sentence (Choi et ...level translation, where a repeated term should keep the same translation throughout the whole ... See full document
6
Exploiting Pre Ordering for Neural Machine Translation
... that source words requiring reordering 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 ... See full document
7
Exploiting Sentential Context for Neural Machine Translation
... the source lan- guage and summarizing its meaning ...a source sentence, they generally scan the sentence to cre- ate a whole understanding, with which in mind they incrementally generate the target sentence ... See full document
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Modeling Source Syntax for Neural Machine Translation
... Due to the capability of carrying syntactic infor- mation in source annotation vectors, we conjec- ture that our model with source syntax is also beneficial for alignment. To test this hypothe- sis, we ... See full document
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Exploiting Linguistic Knowledge for Low-Resource Neural Machine Translation
... Machine translation, which aims to perform transition between distinct languages, is a major focus of NLP research ...the source-side linguistic information as prior knowledge to improve ... See full document
9
Enhancement of Encoder and Attention Using Target Monolingual Corpora in Neural Machine Translation
... the translation qual- ity was improved by increasing the number of synthetic source sentences for a given target sen- tence, and the quality approached that of the man- ual ...diverse source ... See full document
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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
Exploiting Deep Representations for Neural Machine Translation
... Advanced neural machine translation (NMT) models generally implement encoder and de- coder as multiple layers, which allows sys- tems to model complex functions and capture complicated linguistic ... See full document
10
Modeling Target Side Inflection in Neural Machine Translation
... parallel data which contain unseen word forms of known lemmas on the target ...the source language contains translation errors, which may affect trans- lation ...modeling data, but the ... See full document
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Multi Source Neural Machine Translation with Missing Data
... have data in all of the languages that go into our multi- source ...on data that con- tains all of the source ...missing data, such situations using an incomplete multilingual corpus in ... See full document
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