[PDF] Top 20 Recurrent Positional Embedding for Neural Machine Translation
Has 10000 "Recurrent Positional Embedding for Neural Machine Translation" found on our website. Below are the top 20 most common "Recurrent Positional Embedding for Neural Machine Translation".
Recurrent Positional Embedding for Neural Machine Translation
... architecture, positional embeddings are used to encode order dependencies into the input representa- ...a recurrent positional embedding approach based on word ...these recurrent ... See full document
7
Beyond Weight Tying: Learning Joint Input Output Embeddings for Neural Machine Translation
... Tying the weights of the target word em- beddings with the target word classifiers of neural machine translation models leads to faster training and often to better translation quality. Given ... See full document
11
Equalizing Gender Bias in Neural Machine Translation with Word Embeddings Techniques
... The quality of the translation also depends on the professions from the Occupations test and its predicted gender. Again, the system has no prob- lem predicting the gender of professions in the context of “him”, ... See full document
8
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
Multimodal Machine Translation with Embedding Prediction
... Multimodal machine translation is an attrac- tive application of neural machine transla- tion (NMT). It helps computers to deeply understand visual objects and their relations with natural ... See full document
6
Recurrent Neural Network based Rule Sequence Model for Statistical Machine Translation
... n-gram translation model to incorpo- rate lexical dependencies that span rule boundaries (Marino et ...phrase-based translation models to over- come the phrasal independence assumption, but they rely on ... See full document
7
Fast Neural Machine Translation Implementation
... for Neural Machine Translation and Generation by members of the University of Edinburgh, Adam Mickiewicz Univer- sity, Tilde and University of ...the recurrent deep-learning model as imple- ... See full document
6
Deep Recurrent Models with Fast Forward Connections for Neural Machine Translation
... We trained NMT models with depth of 16 in- cluding 25 LSTM layers and evaluated them mainly on the WMT’14 English-to-French translation task. This is the deepest topology that has been in- vestigated in the NMT ... See full document
14
A Recurrent Neural Networks Approach for Estimating the Quality of Machine Translation Output
... John Blatz, Erin Fitzgerald, George Foster, Simona Gan- drabur, Cyril Goutte, Alex Kulesza, Alberto Sanchis, and Nicola Ueffing. 2004. Confidence estimation for machine translation. In Proceedings of the ... See full document
5
Knowledge Based Semantic Embedding for Machine Translation
... In this paper, with the help of knowl- edge base, we build and formulate a se- mantic space to connect the source and target languages, and apply it to the sequence-to-sequence framework to pro- pose a Knowledge-Based ... See full document
10
Non projective Dependency based Pre Reordering with Recurrent Neural Network for Machine Translation
... statistical machine trans- lation performed with phrase based ap- proaches can be increased by permuting the words in the source sentences in an order which resembles that of the target ...rent neural ... See full document
11
Non projective Dependency based Pre Reordering with Recurrent Neural Network for Machine Translation
... statistical machine translation performed with phrase based approaches can be increased by permuting the words in the source sentences in an order which resem- bles that of the target ...of recurrent ... See full document
11
NAVER Machine Translation System for WAT 2015
... We constructed the source word vocabulary with the most common words in the source language corpora. For the target character vocabulary, we used a BI (begin/inside) representation (e.g., 結 /B, 果/I), because it gave ... See full document
5
ReVal: A Simple and Effective Machine Translation Evaluation Metric Based on Recurrent Neural Networks
... As we do not have access to any dataset which provides scores to segments on the basis of trans- lation quality, we used the WMT-13 ranks corpus to automatically derive training data. This corpus is a by-product of the ... See full document
7
Simplifying Neural Machine Translation with Addition Subtraction Twin Gated Recurrent Networks
... Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Lukasz Kaiser, Stephan ... See full document
11
Sentence Embedding for Neural Machine Translation Domain Adaptation
... Recently, Neural Machine Translation (NMT) has set new state-of-the-art benchmarks on many translation tasks (Cho et al., 2014; Bahdanau et al., 2015; Jean et al., 2015; Tu et al., 2016; Mi et ... See full document
7
Machine Translation Evaluation using Recurrent Neural Networks
... The metric uses Glove word vectors (Penning- ton et al., 2014) and the simple LSTM, the de- pendency Tree-LSTM and neural network imple- mentations by Tai et al. (2015). Training is per- formed using a mini batch ... See full document
5
Unsupervised Bilingual Word Embedding Agreement for Unsupervised Neural Machine Translation
... learned translation equivalences between word pairs from two monolingual ...the embedding of the vocabulary for the encoder and decoder of ...naive translation knowledge to enable the ... See full document
11
A Recursive Recurrent Neural Network for Statistical Machine Translation
... Word embedding is usually learnt from large amount of monolin- gual corpus at first, and then fine tuned for spe- cial distinct ...labelling. Recurrent neural networks are leveraged to learn language ... See full document
10
Neural Machine Translation with Recurrent Attention Modeling
... Knowing which words have been attended to in previous time steps while generating a translation is a rich source of information for predicting what words will be attended to in the future. We improve upon the at- ... See full document
5
Related subjects