[PDF] Top 20 Modeling Source Syntax for Neural Machine Translation
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Modeling Source Syntax for Neural Machine Translation
... the source syn- tax to improve the NMT translation accuracy with the expectation of alleviating the issues above in ...each source word with manually designed syn- tactic labels, as Sennrich and ... See full document
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NiuTrans: An Open Source Toolkit for Phrase based and Syntax based Machine Translation
... a unified framework was adopted to decode with different models and ease the implementation of decoding algorithms. Moreover, some useful utilities were distributed with the toolkit, such as: a discriminative reordering ... See full document
6
Unsupervised Source Hierarchies for Low Resource Neural Machine Translation
... adding source hierarchical informa- tion to neural machine translation has used super- vised ...model source syntax. Chen et al. (2017b) enriched source word ... See full document
7
Modeling Target Side Inflection in Neural Machine Translation
... English–German translation: here, the focus is rather put on modeling linguis- tic phenomena, including German word forma- ...make translation challeng- ing; one system variant thus includes simple ... See full document
11
Improved Translation with Source Syntax Labels
... and syntax statistical machine translation have made great progress in the last few years and can claim to represent the state of the art in the ... See full document
9
Relabeling Syntax Trees to Improve Syntax Based Machine Translation Quality
... target translation: the gunman was killed by police ...our source of syntactic information, largely due to the availability of reliable ...output translation has two salient errors: determiner/noun ... See full document
8
Syntax based Multi system Machine Translation
... hybrid machine translation system that explores a parser to acquire syntactic chunks of a source sentence, translates the chunks with multiple online machine translation (MT) system ... See full document
7
Ensemble Learning for Multi Source Neural Machine Translation
... that translation systems from different source language into the same target language have complementary strengths and weak- nesses in terms of translation performance and introduce an approach that ... See full document
10
OpenNMT: Open Source Toolkit for Neural Machine Translation
... One nice aspect of NMT as a model is its rela- tive compactness. When excluding Torch frame- work code, the Lua OpenNMT system including preprocessing is roughly 4K lines of code, and the Python version is less than 1K ... See full document
6
Encoding Source Language with Convolutional Neural Network for Machine Translation
... proposed neural network joint model (NNJM) (Devlin et ...sen source context window, achieving state-of-the-art performance in ...relevant source information through a convolutional architecture ... See full document
11
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 ...sharing neural network framework to ... See full document
11
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- ...lexical ... See full document
6
fairseq: A Fast, Extensible Toolkit for Sequence Modeling
... FAIRSEQ is an open-source sequence model- ing toolkit that allows researchers and devel- opers to train custom models for translation, summarization, language modeling, and other text generation ... See full document
6
Simple and Effective Noisy Channel Modeling for Neural Machine Translation
... the source for prefixes of the ...on source prefixes even though the full source is ...entire source instead of a learned pre- fix length, we simulate different fractions of the source ... See full document
6
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
Syntax Augmented Machine Translation using Syntax Label Clustering
... Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexan- dra Constantin, and Evan ... See full document
7
Neural Machine Translation with Source Side Latent Graph Parsing
... Neural Machine Translation (NMT) is an active area of research due to its outstanding empiri- cal results (Bahdanau et ...improve translation accu- racy (Eriguchi et ...ing syntax-based ... See full document
11
Multi Source Neural Machine Translation with Missing Data
... However, this paradigm assumes that we have data in all of the languages that go into our multi- source system. For example, if we decide that En- glish and Spanish are our input languages and that we would like ... See full document
8
Improved Neural Machine Translation with a Syntax Aware Encoder and Decoder
... of translation, these mechanisms work at the word level and cannot capture phrasal cohe- sion between the two languages (Fox, 2002; Kim et ...the translation more in line with the source syntactic ... See full document
10
Neural Machine Translation with Source Dependency Representation
... Ondˇrej Bojar, Rajen Chatterjee, Christian Feder- mann, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Varvara Logacheva, Christof Monz, Matteo Negri, Aurelie Neveol, Mariana Neves, ... See full document
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