[PDF] Top 20 Incorporating Source Syntax into Transformer Based Neural Machine Translation
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Incorporating Source Syntax into Transformer Based Neural Machine Translation
... a source sentence, but attended only to the words of the ...used syntax to augment the word representations in both RNN-based and Transformer-based NMT; this was done by concatenating ... See full document
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Incorporating Word Reordering Knowledge into Attention based Neural Machine Translation
... between source and target word- ...SMT based on jump distances between the newly translated phras- es and to-be-translated phrases which does not consider specific lexical ... See full document
11
OpenNMT: Neural Machine Translation Toolkit
... Neural machine translation (NMT) is a new methodology for machine translation that has led to remarkable improvements, particularly in terms of human evaluation, compared to ... See full document
8
Incorporating Global Visual Features into Attention based Neural Machine Translation
... attention- based Neural Machine Translation (NMT) models which incorporate visual features into different parts of both the encoder and the ...lutional neural network and are incorpo- ... See full document
12
Incorporating Discrete Translation Lexicons into Neural Machine Translation
... continuous-valued numbers. This is in contrast to more traditional SMT methods such as phrase-based machine translation (PBMT; Koehn et al. (2003)), which represent translations as discrete pairs of ... See full document
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Neural Machine Translation with Source Dependency Representation
... Statistical Machine Translation (PBSMT) implemented in Moses (Koehn et ...only source word representation is ...state-of-the-art syntax enhanced NMT method (Sennrich and Haddow, ... See full document
7
Syntax based Rewriting for Simultaneous Machine Translation
... the source language word ...structure), incorporating the rewrit- ten, more monotonic reference translation into a phrase-based machine translation system enables better ... See full document
10
Improved Neural Machine Translation with a Syntax Aware Encoder and Decoder
... Most neural machine translation (NMT) models are based on the sequential encoder-decoder framework, which makes no use of syntactic ...explicitly incorporating source-side ... See full document
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Syntax Enhanced Neural Machine Translation with Syntax Aware Word Representations
... in neural machine translation ...integrate syntax by rep- resenting 1-best tree outputs from a well- trained parsing system, ...integrate source-side syntax implicitly for ...as ... See full document
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Lattice Based Transformer Encoder for Neural Machine Translation
... Neural machine translation (NMT) takes deterministic sequences for source ...a source sequence with different word segmentors or different subword vocabulary ...model, ... See full document
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Multi Source Transformer for Kazakh Russian English Neural Machine Translation
... We trained en2kk, ru2kk and en2ru SMT sys- tems using Portage (Larkin et al., 2010), a conven- tional log-linear phrase-based SMT system, us- ing the corresponding BPEed parallel corpora pre- pared as described in ... See full document
8
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
10
Graph Convolutional Encoders for Syntax aware Neural Machine Translation
... to incorporating syntactic struc- ture into neural attention-based encoder- decoder models for machine ...of neural networks developed for modeling graph-structured ...of source ... See full document
11
CMU Syntax Based Machine Translation at WMT 2011
... a translation grammar remains the same as in our WMT 2010 ...the source and target parse trees if all word alignments in the yield of s land within the yield of t and vice ... See full document
7
Large aligned treebanks for syntax-based machine translation
... The next step is aligning the nonterminal constituents. Us- ing the Stockholm TreeAligner (Lundborg et al., 2007), we constructed a set of parallel alignments for each language pair which functions as training data for ... See full document
7
Syntax Based Word Ordering Incorporating a Large Scale Language Model
... the syntax-based generation system is weakly analogous to N -gram model insertion for syntax-based statistical machine translation sys- tems, both of which apply a score from the ... See full document
11
Fast Translation Rule Matching for Syntax based Statistical Machine Translation
... tree for compact rule representation and a hyper- tree-based fast algorithm for translation rule matching in a forest-based translation system. We compare our algorithm with two previous ... See full document
9
Efficient retrieval of tree translation examples for Syntax Based Machine Translation
... As the size of bilingual corpus grow larger, the number of translation rules to be stored can easily become unmanageable. As a solution to this prob- lem in the context of phrase-based Machine ... See full document
11
Edinburgh’s Syntax Based Machine Translation Systems
... Galley, M., Graehl, J., Knight, K., Marcu, D., De- Neefe, S., Wang, W., and Thayer, I. (2006). Scalable inference and training of context-rich syntactic translation models. In ACL-44: Pro- ceedings of the 21st ... See full document
7
Binarizing Syntax Trees to Improve Syntax Based Machine Translation Accuracy
... Figure 5 is the actual pipeline that we use for EM binarization. We first generate a packed e-forest via parallel binarization. We then extract minimal translation rules from the (e-forest, f, a)-tuples, pro- ... See full document
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