[PDF] Top 20 Exploiting Linguistic Knowledge for Low-Resource Neural Machine Translation
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Exploiting Linguistic Knowledge for Low-Resource Neural Machine Translation
... Turkish machine translation tasks are shown in Table 5 and Table 6, ...additional linguistic feature input is employed for ...Turkish→English machine translation task, we can see from ... See full document
9
Exploiting Out of Domain Parallel Data through Multilingual Transfer Learning for Low Resource Neural Machine Translation
... In this paper, we work on a linguisti- cally distant and thus challenging language pair Japanese ↔ Russian (Ja ↔ Ru) which has only 12k lines of news domain parallel corpus and hence is extremely resource-poor. ... See full document
12
Transfer Learning for Low Resource Neural Machine Translation
... uses knowledge from a learned task to improve the performance on a related task, typically reducing the amount of required training data (Torrey and Shavlik, 2009; Pan and Yang, ...convolutional neural ... See full document
8
Naive Regularizers for Low-Resource Neural Machine Translation
... for low-resource settings, where the availability of lin- guistic resources can generally not ...improves machine translation quality across multiple low-resource languages, also ... See full document
10
Adaptive Knowledge Sharing in Multi Task Learning: Improving Low Resource Neural Machine Translation
... Figure 2 shows the average percentage of block usage for each task in an MTL model with 3 shared blocks, on the English-Farsi test set. We have ag- gregated the output of the routing network for the blocks in the encoder ... See full document
6
Meta Learning for Low Resource Neural Machine Translation
... performance. Low Resource Translation NMT is known to easily over-fit and result in an inferior performance when the training data is limited (Koehn and Knowles, ...of low resource ... See full document
10
Revisiting Low Resource Neural Machine Translation: A Case Study
... The bulk of research on low-resource NMT has focused on exploiting monolingual data, or par- allel data involving other language pairs. Meth- ods to improve NMT with monolingual data range from the ... See full document
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Copied Monolingual Data Improves Low Resource Neural Machine Translation
... Ondˇrej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Matthias Huck, An- tonio Jimeno Yepes, Philipp Koehn, Varvara Lo- gacheva, Christof Monz, Matteo Negri, Aur´elie N´ev´eol, Mariana Neves, ... See full document
9
Unsupervised Source Hierarchies for Low Resource Neural Machine Translation
... Ondˇrej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Matthias Huck, An- tonio Jimeno Yepes, Philipp Koehn, Varvara Lo- gacheva, Christof Monz, Matteo Negri, Aur´elie N´ev´eol, Mariana Neves, ... See full document
7
Overcoming the Rare Word Problem for low resource language pairs in Neural Machine Translation
... useful resource for many tasks of natural language processing (Kolte and Bhirud, 2008; Méndez ...our knowledge, none of the work ex- ploits the benefits of WordNet in order to ease the rare word problem in ... See full document
8
Exploiting Sentential Context for Neural Machine Translation
... gain linguistic insights into the global and deep sentence representation, we conducted prob- ing tasks 1 (Conneau et ...guistics knowledge embedded in the encoder out- put and the sentence representation ... See full document
7
Exploiting Multilingualism through Multistage Fine Tuning for Low Resource Neural Machine Translation
... Fine-tuning based transfer learning has been studied for transferring proper parameters (Zoph et al., 2016; Gu et al., 2018b), lexical (Zoph et al., 2016; Nguyen and Chiang, 2017; Gu et al., 2018a; Lakew et al., 2018), ... See full document
7
Exploiting Linguistic Resources for Neural Machine Translation Using Multi task Learning
... We evaluated models that are trained both on 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 (ca. ... See full document
10
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 ... See full document
12
Transfer Learning across Low Resource, Related Languages for Neural Machine Translation
... a low-resource ...a low-resource language pair by exploiting its lexical similarity with another related, low-resource ... See full document
6
Linguistic Input Features Improve Neural Machine Translation
... of neural machine translation. On the one hand, the machine learning capability of neural architectures is likely to increase, decreasing the benefit pro- vided by the features we ... See full document
9
NICT’s participation to WAT 2019: Multilingualism and Multi step Fine Tuning for Low Resource NMT
... Neural machine translation (NMT) (Cho et ...alignments, translation rules, and complicated decoding algorithms, which are the characteris- tics of phrase-based statistical machine ... See full document
5
Incremental Domain Adaptation for Neural Machine Translation in Low Resource Settings
... on translation time and quality of incremental model ...post-edit translation candidates, translations that improve over time might reduce this post- editing effort and, consequently reduce the over- all ... See full document
10
Target Conditioned Sampling: Optimizing Data Selection for Multilingual Neural Machine Translation
... Multilingual NMT has led to impressive gains in translation accuracy of low-resource lan- guages (LRL) (Zoph et al., 2016; Firat et al., 2016; Gu et al., 2018; Neubig and Hu, 2018; Nguyen and Chiang, ... See full document
6
Exploiting Deep Representations for Neural Machine Translation
... Deep representations have proven to be of pro- found value in machine translation (Meng et al., 2016; Zhou et al., 2016). Multiple-layer encoder and decoder are employed to perform the transla- tion task ... See full document
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