[PDF] Top 20 Improving a Multi Source Neural Machine Translation Model with Corpus Extension for Low Resource Languages
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Improving a Multi Source Neural Machine Translation Model with Corpus Extension for Low Resource Languages
... training corpus, we used an OPUS English-Arabic corpus, which contains 11 million sentences, to generate a synthetic Korean-Arabic ...the source side or target ...English-Arabic translation ... See full document
5
Zero Resource Translation with Multi Lingual Neural Machine Translation
... the multi-way, multilin- gual neural translation model by Firat et ...many languages in order to better translate when a source sentence is given in multiple lan- ...of ... See full document
10
Addressing word order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages
... for Neural Ma- chine Translation (NMT) trains a NMT model on an assisting language-target language pair (parent model) which is later fine-tuned for the source language-target language ... See full document
6
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
Trivial Transfer Learning for Low Resource Neural Machine Translation
... for neural machine transla- tion under low-resource ...“parent” model for a high-resource language pair and then continue the training on a low- resource pair only ... See full document
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Improving Robustness of Neural Machine Translation with Multi task Learning
... of multi-task learning for machine translation, Tu et ...the source sen- tence from the hidden layers of the translation de- ...plete source information, which helps improve the ... See full document
7
A study of attention based neural machine translation model on Indian languages
... of low- resource language pairs for which sufficiently large parallel corpora is not available and the language pairs whose syntaxes differ ...the languages as it tends to increase the number of ... See full document
10
Transfer Learning across Low Resource, Related Languages for Neural Machine Translation
... two source languages but also ensure consistency be- tween source and target segmentation among each language pair, we learn the rules from the union of source and target data of both the ... See full document
6
Data Augmentation for Low Resource Neural Machine Translation
... encoder-decoder model as described in (Lu- ong et ...cess source and target language data with Byte- pair encoding (BPE) (Sennrich et ...word translation in con- ...alter source sentences ... See full document
7
Multi Source Neural Machine Translation with Missing Data
... We describe the settings of common parts for all NMT models: multi-encoder NMT, mixture of NMT experts, and one-to-one NMT. We used global attention and attention feeding (Luong et al., 2015) for the NMT models ... See full document
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Exploiting Linguistic Knowledge for Low-Resource Neural Machine Translation
... 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 ... See full document
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Meta Learning for Low Resource Neural Machine Translation
... introduced model-agnostic meta-learning al- gorithm (MAML, Finn et ...for low- resource neural machine translation ...frame low-resource translation as a ... See full document
10
Transfer Learning for Low Resource Neural Machine Translation
... training corpus of about 8m English words for the low-resource experiments, and Firat et ...both low-resource and high-resource lan- guages, while in our case the datasets come ... See full document
8
Multi lingual neural title generation for e Commerce browse pages
... the extension of our work from a single-language setting to multi- language ...target neural machine translation from multiple source languages into a single tar- get ... See full document
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Diversify and Combine: Improving Word Alignment for Machine Translation on Low Resource Languages
... statistical machine translation (SMT) ...The resource required for this approach is little, compared to what is needed to build a rea- sonable discriminative alignment model, for ex- ...on ... See full document
5
Universal Neural Machine Translation for Extremely Low Resource Languages
... the model con- fuses "india" and "china" as they may have close representation in the mono-lingual ...same source sentence with various auxiliary ...auxiliary languages based on their ... See full document
11
Neural Machine Translation of Low Resource and Similar Languages with Backtranslation
... the source language with a pre-existing target-to-source translation ...noisy source translations are then incorporated to train a new source-to-target MT system (Sennrich et ... See full document
12
Unsupervised Source Hierarchies for Low Resource Neural Machine Translation
... Incorporating source syntactic infor- mation into neural machine translation (NMT) has recently proven success- ful (Eriguchi et ...for languages or domains for which a reliable parser ... See full document
7
Improving Low Resource Neural Machine Translation with Filtered Pseudo Parallel Corpus
... language model and the translation model (Wang et ...better translation performance and reduce time- complexity with a small high-quality ...tween source and target ... See full document
9
Adaptive Knowledge Sharing in Multi Task Learning: Improving Low Resource Neural Machine Translation
... Neural Machine Translation (NMT) is no- torious for its need for large amounts of bilingual ...is Multi- Task Learning (MTL) to leverage differ- ent linguistic resources as a source of ... See full document
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