[PDF] Top 20 Machine Translation Evaluation using Recurrent Neural Networks
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Machine Translation Evaluation using Recurrent Neural Networks
... and machine trans- lation (Mikolov et ...Deep Neural Networks (DNNs) or Re- current Neural Networks (RNNs) are able to cap- ture semantic similarity for words (Mikolov et ...this ... See full document
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ReVal: A Simple and Effective Machine Translation Evaluation Metric Based on Recurrent Neural Networks
... and machine trans- lation (Mikolov et ...Deep Neural Networks (DNNs) or RNNs are able to capture semantic similarity for words (Mikolov et ...MT evaluation metrics can only achieve this ... See full document
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Recurrent Neural Network based Tuple Sequence Model for Machine Translation
... prior neural network-based translation models either employ feed-forward neural networks to ex- plicitly integrate source information via word-to-word alignment, or use recurrent ... See full document
10
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 ...for evaluation, thereby side stepping the algorithmic and ... See full document
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Pairwise Neural Machine Translation Evaluation
... These human quality judgments can be used to train automatic metrics. This supervised learning can be oriented to predict absolute scores, e.g., us- ing regression (Albrecht and Hwa, 2008), or rank- ings (Duh, 2008; Song ... See full document
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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
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Paraphrasing Revisited with Neural Machine Translation
... of neural machine translation, a new approach to machine transla- tion based purely on neural networks (Kalchbren- ner and Blunsom, 2013; Bahdanau et ...deep neural ... See full document
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Document Context Neural Machine Translation with Memory Networks
... document-level neural ma- chine translation model which takes both source and target document context into account using memory ...a neural translation model equipped with two memory ... See full document
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Equalizing Gender Bias in Neural Machine Translation with Word Embeddings Techniques
... We did our study in the domain of news articles and professions. However, human corpora has a broad spectrum of categories, as an instance: in- dustrial, medical, legal that may rise other biases particular to each area. ... See full document
8
Additive Neural Networks for Statistical Machine Translation
... statistical machine translation (SMT) systems are modeled using a log- linear ...A neural network is a reasonable method to address these ...a neural network is not trivial, especially ... See full document
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Low Resource Machine Transliteration Using Recurrent Neural Networks of Asian Languages
... as machine trans- lation in the transliteration task for the English- Vietnamese low-resource language pair, with a performance of 63 BLEU ...by using alignment representation for in- put sequences and ... See full document
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Memory Augmented Neural Networks for Machine Translation
... We have proposed a series of MANN in- spired models for machine translation. Two of these models; NTM Style Attention and the Memory-Augmented Decoder extend the atten- tional encoder-decoder which has ... See full document
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Recurrent Stacking of Layers for Compact Neural Machine Translation Models
... Eventually, using a different layer stacking config- uration for training and decoding leads to only sub-optimal results and thus we conclude that in its current form, the RS-NMT is unable to generalize the ... See full document
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A Recursive Recurrent Neural Network for Statistical Machine Translation
... training using ear- ly update ...a translation phrase pair, we initialize the phrase pair embedding by leveraging the sparse features and recurrent neural ...in translation table, and ... See full document
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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
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Simplifying Neural Machine Translation with Addition Subtraction Twin Gated Recurrent Networks
... We used 1000 hidden units for both encoder and decoder. All word embeddings had dimensional- ity 620. We initialized all model parameters ran- domly according to a uniform distribution ranging from -0.08 to 0.08. These ... See full document
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Recurrent Positional Embedding for Neural Machine Translation
... a recurrent positional embedding approach based on word ...these recurrent positional embeddings are learned by a recurrent neural network, encoding word content-based order dependencies into ... See full document
7
Neural Machine Translation with Recurrent Attention Modeling
... a recurrent neural network to summarize the pre- ceding attentions which could impact the attention of the current decoding ...that using a larger context attention win- dow would result in a better ... See full document
5
Bidirectional Generative Adversarial Networks for Neural Machine Translation
... However, in this training process, the discrim- inator typically suffers from inadequate training problem, leading to the instability of GAN train- ing. In practice, sampling large translation candi- dates is ... See full document
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Impact of Earnings per Share on Market Price of Share with Special Reference to Selected Companies Listed on NSE
... of machine learning techniques based on learning representations of ...deep neural networks, convolutional deep neural networks, deep belief networks and recurrent ... See full document
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