[PDF] Top 20 Sequence to Dependency Neural Machine Translation
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Sequence to Dependency Neural Machine Translation
... generated translation and its corresponding dependency ...the translation of SMT is disfluent and ungram- matical, whereas RNNsearch is better than ...the translation of RNNsearch is locally ... See full document
10
Recurrent Neural Network based Rule Sequence Model for Statistical Machine Translation
... in machine translation, Ding and Palmer (2005) use n-gram rule Markov model in the dependency treelet model, Liu and Gildea (2008) applies the same method in a tree-to- string ...rent neural ... See full document
7
A Comparison of Two Paraphrase Models for Taxonomy Augmentation
... in neural net- works for machine translation, seq2seq models with attention representing input as a sequence of characters (Hasan et ...with neural machine trans- lation, where ... See full document
6
Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets
... Chinese-English translation task. Table 3 presents the translation performance of the BR- CSGAN on the test sets when the N are set from 5 to 30 with interval ...the translation performance of the ... See full document
10
Parallelizable Stack Long Short Term Memory
... ing dependency parsing (Dyer et ...and neural machine translation (Eriguchi et ...the neural network architectures used to build tree-structured representations are not able to exploit ... See full document
6
Hybrid Data Model Parallel Training for Sequence to Sequence Recurrent Neural Network Machine Translation
... Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Ma- cherey, Jeff Klingner, Apurva Shah, Melvin John- son, Xiaobing Liu, Łukasz Kaiser, ... See full document
9
Recurrent Neural Network based Tuple Sequence Model for Machine Translation
... recurrent neural network-based tuple sequence model (RNNTSM) that can help phrase-based translation model overcome the phrasal independence ... See full document
10
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
Non projective Dependency based Pre Reordering with Recurrent Neural Network for Machine Translation
... includes dependency informa- tion, but not the full information of reorder- ing fragments as defined by our automa- ton model ...to machine translation pre-reordering, we pro- pose an extension, ... See full document
11
Character based Decoding in Tree to Sequence Attention based Neural Machine Translation
... correct sequence of characters “ ”, “ ”, and “ ” one by ...the translation of the word “380” into the characters“ ”, so the character-based model can be trained without copy mechanism (Ling et ... See full document
9
A Neural, Interactive predictive System for Multimodal Sequence to Sequence Tasks
... a neural interactive-predictive system for tackling mul- timodal sequence to sequence ...to sequence tasks: machine translation, image and video ... See full document
6
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
7
An Operation Sequence Model for Explainable Neural Machine Translation
... Despite considerable consensus about the im- portance of word alignments in practice (Koehn and Knowles, 2017), e.g. to enforce constraints on the output (Hasler et al., 2018) or to preserve text formatting, introducing ... See full document
12
A Deep Learning Based Approach to Transliteration
... different neural machine translation (NMT) frameworks: recurrent neural net- work and convolutional sequence to se- quence based ... See full document
5
Tree to Sequence Attentional Neural Machine Translation
... Decoding in the NMT models is a generative pro- cess and depends on the target language model given a source sentence. The score becomes smaller as the target sentence becomes longer, and thus the simple beam search does ... See full document
11
Tutorial: De mystifying Neural MT
... Neural Statistical Machine Translation Neural Machine Translation Encoder Decoder Sequence-to-sequence learning: Encoder Sequence-to-sequence learning: Decoder Let’s use a simple NN for [r] ... See full document
84
Improving Sequence to Sequence Neural Machine Translation by Utilizing Syntactic Dependency Information
... In this work, we proposed a method in which the Seq2Dep NMT model is trained by utilizing syn- tactic dependencies to provide the model more abundant information. In other words, Seq2Dep model learns the potential ... See full document
9
Distilling Knowledge for Search based Structured Prediction
... In Section 4.2, improvements from distilling the ensemble have been witnessed in both the transition-based dependency parsing and neural machine translation experiments. However, ques- tions ... See full document
10
NAVER Machine Translation System for WAT 2015
... Table 3 shows effects of our NMT model. “Hu- man” indicates the pairwise crowdsourcing eval- uation scores provided by WAT 2015 organiz- ers. In the table, “T2S/PBMT only” is the fi- nal T2S/PBMT systems shown in section ... See full document
5
Quadratic Time Dependency Parsing for Machine Translation
... other machine translation ex- periments that do not require chart ...phrase-based translation models to associate each word with a supertag, which con- tains most of the information needed to build a ... See full document
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