[PDF] Top 20 On the Properties of Neural Machine Translation: Encoder–Decoder Approaches
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On the Properties of Neural Machine Translation: Encoder–Decoder Approaches
... A number of recent papers have proposed to use neural networks to directly learn the condi- tional distribution from a bilingual, parallel cor- pus (Kalchbrenner and Blunsom, 2013; Cho et al., 2014; Sutskever et ... See full document
9
Chunk based Decoder for Neural Machine Translation
... as machine translation (Luong and Manning, 2016), document modeling (Li et ...hierarchical encoder-decoder models, but not for the purpose of learning syntactic structures of target ... See full document
12
A Tree based Decoder for Neural Machine Translation
... RNN encoder, producing the hidden ...last encoder hidden state computes the prob- ability distribution over all CFG rules whose left hand side (LHS) is Root, and selects a rule to apply to the ... See full document
6
Understanding and Improving Morphological Learning in the Neural Machine Translation Decoder
... the decoder learns considerably less morphology than the encoder in the NMT archi- ...the decoder needs assis- tance from the encoder and the attention mecha- nism to generate correct target ... See full document
10
A Character Aware Encoder for Neural Machine Translation
... vocabulary-specific approaches, the unit-specific approaches try to use more fine- grained processing units than words, like sub-word units (Sennrich et ... See full document
8
Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input
... Autoregressive Neural Machine Translation Deep neural network with encoder-decoder framework has achieved great success on machine translation, with differ- ent ... See full document
8
A Convolutional Encoder Model for Neural Machine Translation
... the encoder to the efficiency of the ...lutional encoder increases the speed of the overall model by a factor of ...BiLSTM encoder while improving accuracy by ... See full document
13
Recycling a Pre trained BERT Encoder for Neural Machine Translation
... BERT encoder was ...is, decoder training and fine-tuning, because the number of unlearned pa- rameters was as large as the number of pre-trained model ... See full document
9
LIG CRIStAL Submission for the WMT 2017 Automatic Post Editing Task
... of Neural Machine Translation (NMT) models (Sutskever et ...use encoder-decoder ap- proaches (Junczys-Dowmunt and Grundkiewicz, 2016, 2017; Libovick´y et ...These ... See full document
7
Doubly Attentive Decoder for Multi modal Neural Machine Translation
... the decoder RNN and before emitting a target ...the encoder bidirectional and the de- coder RNN using one same mask in all time ...The translation quality of our models is eval- uated quantitatively ... See full document
12
Incorporating Source Syntax into Transformer Based Neural Machine Translation
... into neural machine translation without requiring a specific NMT ...single encoder and different decoders to train two tasks: parsing the source sentence and translating from source to ...RNN ... See full document
10
Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
... RNN Encoder– Decoder that consists of two recurrent neural networks ...The encoder and de- coder of the proposed model are jointly trained to maximize the conditional prob- ability of a target ... See full document
11
Self Attentive Residual Decoder for Neural Machine Translation
... Table 2 shows BLEU values calculated by multi- bleu, and includes the NMT system proposed by Luong et al. (2015) which replaces unknown pre- dicted words with the most strongly aligned word on the source sentence. Also, ... See full document
14
Large Scale Transfer Learning for Natural Language Generation
... deep neural language ...ize encoder and decoder in a seq2seq model for machine translation ...zero-shot machine translation used large corpora of mono- lingual data to ... See full document
6
Still not there? Comparing Traditional Sequence to Sequence Models to Encoder Decoder Neural Networks on Monotone String Translation Tasks
... spelling correction, G2P conversion, and lemmatization. Monotone Seq2Seq tasks such as morpho- logical analysis/lemmatization, grapheme-to-phoneme conversion (G2P) (Yao and Zweig, 2015; Rao et al., 2015), transliteration ... See full document
12
Tied Transformers: Neural Machine Translation with Shared Encoder and Decoder
... in neural machine trans- lation (briefly, NMT) for similar languages ...and decoder of an NMT model. We share the encoder and decoder of Transformer (Vaswani et ...English ... See full document
8
Hybrid Machine Translation with Multi-Source Encoder-Decoder Long Short-Term Memory in English-Malay Translation
... Statistical Machine Translation (SMT) and Neural Machine Translation (NMT) are the state-of-the-art approaches in machine translation ...The translation ... See full document
7
Memory enhanced Decoder for Neural Machine Translation
... for decoder without exter- nal memory, rendering direct optimization over all the parameters rather ...of encoder and parameters of M EM D EC , except those related to ... See full document
9
Montreal Neural Machine Translation Systems for WMT’15
... MILA neural machine trans- lation (NMT) systems for WMT’15, using the encoder–decoder model with the attention mech- anism (Bahdanau et ...for neural machine ...other ... See full document
7
Improved Neural Machine Translation with a Syntax Aware Encoder and Decoder
... We also extend the decoder to incorporate infor- mation about the source syntax into the attention model. We have observed two issues in transla- tions produced using the tree encoder. First, a syn- tactic ... See full document
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