[PDF] Top 20 Multi Source Neural Machine Translation with Missing Data
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Multi Source Neural Machine Translation with Missing Data
... TED data in de- tail to investigate the mixed results ...test data, separating the results for com- plete and incomplete multilingual ...all source sentences are present in the test data, ... See full document
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Incorporating Source Syntax into Transformer Based Neural Machine Translation
... corporating source-side syntactic annotations into a Transformer-based neural machine translation ...first, multi-task, used a shared en- coder and decoder to train two tasks: transla- ... See full document
10
Target Foresight Based Attention for Neural Machine Translation
... in neural machine translation, an attention model is used to identify the aligned source words for a target word target foresight word in order to select translation con- text, but it ... See full document
11
Neural Machine Translation with Source Side Latent Graph Parsing
... novel neural ma- chine translation model which jointly learns translation and source-side latent graph representations of ...ral machine translation model, and thus the parser is ... See full document
11
Unsupervised Source Hierarchies for Low Resource Neural Machine Translation
... jecting source syntax into NMT requires parsing the training data with an external parser, and such parsers may be unavailable for low-resource lan- ...syntactic source information may improve ... See full document
7
Using Target side Monolingual Data for Neural Machine Translation through Multi task Learning
... of Neural Machine Trans- lation (NMT) models relies heavily on the availability of sufficient amounts of paral- lel data, and an efficient and effective way of leveraging the vastly available amounts ... See full document
6
Improving a Multi Source Neural Machine Translation Model with Corpus Extension for Low Resource Languages
... the source side or target ...the source sides, OPUS was used to obtain a good target ...English-Korean translation model 2 translates English sentences of an OPUS English-Arabic corpus into Korean ... See full document
5
Zero Resource Translation with Multi Lingual Neural Machine Translation
... of source sen- tences in Spanish (Es) and French (Fr) to English ...any multi-way parallel ...the translation quality (mea- sured in BLEU) by 3 points in the case of the test set (compare Table 2 ... See full document
10
A Multi Task Architecture on Relevance based Neural Query Translation
... a multi-task learning approach to train a Neural Machine Translation (NMT) model with a Relevance-based Auxiliary Task (RAT) for search query ...parallel data is not aware of the ... See full document
6
Improving Neural Machine Translation Models with Monolingual Data
... dummy source context was successful to some ex- tent, but we achieve substantial gains in all tasks, and new SOTA results, via back-translation of monolingual target data into the source ... See full document
11
Attention Focusing for Neural Machine Translation by Bridging Source and Target Embeddings
... NMT translation, in our new bridging approach we do not use extra re- sources in the NMT model, but let the model itself learn the similarity of word pairs from the training ... See full document
10
Adapting Neural Machine Translation with Parallel Synthetic Data
... synthetic data in our ...different translation methods or technolo- gies when translating the monolingual ...adding source synthetic data instead of target synthetic data affects the ... See full document
10
Exploiting Monolingual Data at Scale for Neural Machine Translation
... back translation (BT) approach to leverage the target-side monolingual data, which is simple and ...monolingual data. The translation output and the target-side monolingual data then ... See full document
10
Multi agent Learning for Neural Machine Translation
... To resolve the second problem, we simplify the many-to-many learning to the one-to-many (one teacher vs. many students) learning, extending ensemble knowledge distillation (Fukuda et al., 2017; Freitag et al., 2017; Liu ... See full document
10
Data Augmentation for Low Resource Neural Machine Translation
... training data for NMT. Next we observe that both back-translation and our proposed TDA method significantly improve translation ...back- translation in all test ...costly translation ... See full document
7
Soft Contextual Data Augmentation for Neural Machine Translation
... contextual data augmentation, a simple yet effective data augmen- tation approach for ...training data by replacing a randomly chosen word in a sentence with a soft word, which is a probabilis- tic ... See full document
6
OpenNMT: Open Source Toolkit for Neural Machine Translation
... Factored Neural Translation In feature-based factored neural translation (Sen- nrich and Haddow, 2016), instead of generating a word at each time step, the model generates both word and ... See full document
6
Multi Source Transformer for Kazakh Russian English Neural Machine Translation
... Russian-English data we used in our systems consists of web-crawled data, news commentary data and Wikipedia article ...these data were used to train the foundation sys- tems for ...bilingual ... See full document
8
Exploiting Source side Monolingual Data in Neural Machine Translation
... monolingual data in conventional statistical ma- chine translation (SMT) (Koehn et ...monolingual data so as to boost the transla- tion ...monolingual data. In con- trast, the ... See full document
11
Multi Source Neural Translation
... The above work all relies on base MT systems trained on bilingual data, using traditional meth- ods. This follows early work in sentence align- ment (Gale and Church, 1993) and word alignment (Simard, 1999), which ... See full document
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