[PDF] Top 20 A Recursive Recurrent Neural Network for Statistical Machine Translation
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A Recursive Recurrent Neural Network for Statistical Machine Translation
... labelling. Recurrent neural networks are leveraged to learn language model, and they keep the history information circularly inside the network for arbitrarily long time (Mikolov et ...2010). ... See full document
10
Non projective Dependency based Pre Reordering with Recurrent Neural Network for Machine Translation
... Fully statistical approaches, on the other hand, learn the reordering relation from word alignments. Some of them learn reordering rules on the constituency (Dyer and Resnik, 2010) (Khalilov and Fonollosa, 2011) ... See full document
11
Additive Neural Networks for Statistical Machine Translation
... the translation model (Nguyen et ...the translation per- formance may not improve, or may even decrease, after one integrates additional features into the ...the translation performance, but after a ... See full document
11
Non projective Dependency based Pre Reordering with Recurrent Neural Network for Machine Translation
... Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondˇrej Bojar, Alexandra Constantin, and Evan ... See full document
11
Machine Translation Evaluation using Recurrent Neural Networks
... Recurrent Neural Networks allow processing of arbitrary length sequences, but early RNNs had the problem of vanishing and exploding gradi- ents (Bengio et ... See full document
5
Neural Network Based Bilingual Language Model Growing for Statistical Machine Translation
... Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertol- di, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexan- dra Constantin, and Evan ... See full document
7
Residual Stacking of RNNs for Neural Machine Translation
... The network architectures of NMT models are simple but ...the translation from the vector of sentence repre- ...single recurrent neural network ... See full document
7
English Basque Statistical and Neural Machine Translation
... auxiliary network. Like with any other neural models for NLP, prior to processing each unique word in the cor- pus needs to be mapped to a high-dimensional vector (word ... See full document
6
Hybrid Data Model Parallel Training for Sequence to Sequence Recurrent Neural Network Machine Translation
... We have proposed a hybrid data-model parallel approach for Seq2Seq RNN MT. We applied model parallelism to the encoder-decoder part and data parallelism to the attention-softmax part. The experimental results show that ... See full document
9
Recurrent Stacking of Layers for Compact Neural Machine Translation Models
... Another probable explanation lies in the understanding of what Recurrent Neural Networks (RNN), such as LSTMs (Hochreiter and Schmidhuber 1997) do. At each time-step, an RNN refines the representation of a ... See full document
8
Translation Quality Estimation using Recurrent Neural Network
... The approach is language independent and it uses only context words’ vector for predicting the tag for a word. In the other words, we check if any word fits (grammatically) in the given slot of words or not. We could use ... See full document
6
Recurrent Neural Network based Translation Quality Estimation
... cehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014. Learning phrase representations using rnn encoder–decoder for statistical machine translation. In Proceedings of the ... See full document
6
Hybrid Neural Network Alignment and Lexicon Model in Direct HMM for Statistical Machine Translation
... a neural network to automatically learn features (as we do in this ...used neural network-based lexicon and alignment models inside the HMM alignment model, but they model alignments using a ... See full document
7
Abstractive Compression of Captions with Attentive Recurrent Neural Networks
... In this paper we have described a method for gener- ating abstractive compressions of scene description using attention-based bidirectional LSTMs (aRNN) trained on a new large dataset created from paired long and short ... See full document
10
Converting Continuous Space Language Models into N Gram Language Models for Statistical Machine Translation
... Another approach is using restricted Boltzmann machines (RBMs) (Niehues and Waibel, 2012) instead of using multi-layer neural networks (Bengio et al., 2003; Schwenk, 2007; Le et al., 2011). Since probability in a ... See full document
6
Reference Network for Neural Machine Translation
... Models We evaluate our RefNet with different structures on Zh-En and En-De. For Zh-En we choose the typical attention-based recurrent NMT model (Bahdanau et al., 2015) as initialization, which consists of a ... See full document
11
Recurrent Positional Embedding for Neural Machine Translation
... Transformer translation systems (Vaswani et al., 2017), without recurrent and convolutional neural networks, rely on a positional embedding (PE) approach to encode order information into the input ... See full document
7
Bilingual Correspondence Recursive Autoencoder for Statistical Machine Translation
... of machine translation and cross-lingual in- formation processing, bilingual embedding learn- ing has become an increasingly important ...and translation models (Tran et ...the recursive and ... See full document
11
Fast and Robust Neural Network Joint Models for Statistical Machine Translation
... basic neural network ar- chitecture and a lexicalized probability model to create a powerful MT decoding ...ral network joint model (NNJM), which augments an n-gram target language model with an ... See full document
11
NAVER Machine Translation System for WAT 2015
... Neural machine translation (NMT) is a new ap- proach to machine translation that has shown promising results compared to the existing ap- proaches such as phrase-based ... See full document
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