[PDF] Top 20 Translation Quality Estimation using Recurrent Neural Network
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Translation Quality Estimation using Recurrent Neural Network
... QE using the CRF++ tool with data selection and data bootstrapping in which data selection filters out the sentences having the smallest proportion of erroneous tokens and are assumed to be less use- ful for the ... See full document
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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 2014 ... See full document
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Improving Machine Translation Quality Estimation with Neural Network Features
... Machine translation quality estimation is a challenging task in the WMT evaluation ...matic quality estimation, and in this paper, we propose neural network fea- tures, ... See full document
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SHEF NN: Translation Quality Estimation with Neural Networks
... We have proposed several novel features for trans- lation quality estimation, which are trained with the use of neural networks. When added to large standard feature sets for Task 1, the CSLM fea- ... See full document
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Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation
... introduced neural network translation systems suffer from a significant drop in translation quality when translating long sentences, unlike existing phrase-based translation ... See full document
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Predicting Hurricane Trajectories Using a Recurrent Neural Network
... Hyperparameters are preset values optimally selected by the programmers before training begins. The activated values of hyperparameters vary greatly depending on the model being employed, the quantity and quality ... See full document
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Recurrent Neural Network based Tuple Sequence Model for Machine Translation
... to-word translation probabilities (such as “musicians:musiciens” in the example of Section 2) for those non-one-to-one ...the translation system will have a translation option for an isolated ... See full document
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An Empirical Evaluation of Noise Contrastive Estimation for the Neural Network Joint Model of Translation
... NNJM training data is pre-processed to limit vo- cabularies to 16K types for source or target inputs, and 32K types for target outputs. We build 400 deterministic word clusters for each corpus using mkcls (Och, ... See full document
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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 ... See full document
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Investigations on Phrase based Decoding with Recurrent Neural Network Language and Translation Models
... We observe that integrating RNN models into phrase-based decoding slightly outperforms ap- plying them in a rescoring step. This is unlike the case of feedforward networks, which where integrated into phrase-based ... See full document
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Text Classification using Recurrent Neural Network in Quora
... the translation process between computers and ...language translation, information retrieval and artificial ...language translation software because language is constantly ... See full document
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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
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A Recurrent Neural Networks Approach for Estimating the Quality of Machine Translation Output
... a recurrent neural net- works approach for estimating the quality of ma- chine translation output at sentence level, which does not require manual effort for finding the best relevant ... See full document
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Joint Language and Translation Modeling with Recurrent Neural Networks
... on neural networks for speech recognition or machine translation used a rescoring setup based on n-best lists (Arisoy et ...of translation hypotheses in polynomial ...a recurrent neural ... See full document
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A Recursive Recurrent Neural Network for Statistical Machine Translation
... recursive neural network and recurrent neural network, and in turn integrates their respective capabilities: (1) new information can be used to generate the next hidden state, like ... See full document
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Abstractive Compression of Captions with Attentive Recurrent Neural Networks
... description using attention-based bidirectional LSTMs (aRNN) trained on a new large dataset created from paired long and short image ...Machine Translation system (Moses) and a Human written short scene de- ... See full document
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Recurrent Neural Network Grammars
... Sequential recurrent neural networks (RNNs) are remarkably effective models of natural ...obtained using RNNs (Zaremba et ...machine translation (Bahdanau et ... See full document
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A Deep Learning Based Approach to Transliteration
... ral network based deep learning architec- tures for the transliteration of named en- ...different neural machine translation (NMT) frameworks: recurrent neural net- work and ... See full document
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Computational Analysis of Sag and Swell in Electrical Power Supply Network
... the estimation and complete analysis of the two main power quality factors (sags and swells) using Neural ...power quality (PQ) disturbances include sag, swell, harmonics, transients, ... See full document
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Bidirectional Recurrent Convolutional Neural Network for Relation Classification
... Two-Channel Recurrent Neural Network with Long Short Term Memory Units The recurrent neural network is suitable for mod- eling sequential data, as it keeps hidden state vec- tor ... See full document
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