[PDF] Top 20 CytonMT: an Efficient Neural Machine Translation Open source Toolkit Implemented in C++
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CytonMT: an Efficient Neural Machine Translation Open source Toolkit Implemented in C++
... Rico Sennrich, Orhan Firat, Kyunghyun Cho, Alexan- dra Birch, Barry Haddow, Julian Hitschler, Marcin Junczys-Dowmunt, Samuel L”aubli, Antonio Vale- rio Miceli Barone, Jozef Mokry, and Maria Nadejde. 2017. Nematus: a ... See full document
6
OpenNMT: Open Source Toolkit for Neural Machine Translation
... the source RNN with a deep convolution over the source ...also open-sourced as ...been implemented directly in OpenNMT by replacing the source encoder with a Pyrimidal source ... See full document
6
The Sockeye Neural Machine Translation Toolkit at AMTA 2018
... popular open-source toolkits on two language directions: English into German (EN → DE) and Latvian into English ...on Machine Translation [Bojar et al., 2017]. We ran each toolkit in a ... See full document
8
LeafNATS: An Open Source Toolkit and Live Demo System for Neural Abstractive Text Summarization
... from source articles, such as encoder-decoder framework (Sutskever et ...as machine translation (Bahdanau et ...an open-source toolbox that modularizes dif- ferent network components ... See full document
6
NiuTrans: An Open Source Toolkit for Phrase based and Syntax based Machine Translation
... We implemented the toolkit in C++ language, with special consideration of extensibility and ...efficiency. C++ enables us to develop efficient translation engines which have high ... See full document
6
Parsing-based Machine Translation using an Open Source Toolkit: Joshua for Tamil Language
... In addition to the distributed LM mentioned above, implement three local n-gram language models. Specifically, A straightforward implementation of the n-gram scoring function in Java is provided. This Java implementation ... See full document
5
Exploring Recombination for Efficient Decoding of Neural Machine Translation
... The proposed method was evaluated on two trans- lation tasks: NIST Chinese-English (Zh-En) and WMT English-German (En-De). For Zh-En, the training set comprised 1.4M sentences pairs from LDC corpora. NIST 02 was selected ... See full document
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Neural Machine Translation with Source Dependency Representation
... Statistical Machine Translation (PBSMT) implemented in Moses (Koehn et ...only source word representation is ...Nematus toolkit 4 (Sennrich et ... See full document
7
INMT: Interactive Neural Machine Translation Prediction
... the toolkit and still keeping the interac- tion ...our translation backend is that it is highly efficient, modular, extensible and well doc- ... See full document
6
OpenNMT: Neural Machine Translation Toolkit
... an open-source toolkit for developing neural machine translation systems, known as OpenNMT ...core translation tasks, OpenNMT was designed with two aims: (a) prioritize ... See full document
8
Introducing CURRENNT: The Munich Open-Source CUDA RecurREnt Neural Network Toolkit
... as open-source C++ code (Graves, ...many machine learning algorithms including LSTM-RNN has been introduced by Schaul et ...the source code is not ... See full document
5
Incorporating Source Syntax into Transformer Based Neural Machine Translation
... corporating source-side syntactic annotations into a Transformer-based neural machine translation ...the source sentences as well as unparsed source sentences directly into the ... See full document
10
NeuralClassifier: An Open source Neural Hierarchical Multi label Text Classification Toolkit
... • Suitable for almost all text classification tasks: NeuralClassifier is designed for hierarchi- cal and multi-label classification, which naturally also supports binary-class and multi-class clas- sification, so it can ... See full document
6
Unsupervised Source Hierarchies for Low Resource Neural Machine Translation
... Incorporating source syntactic infor- mation into neural machine translation (NMT) has recently proven success- ful (Eriguchi et ...for neural machine translation; this ... See full document
7
Ensemble Learning for Multi Source Neural Machine Translation
... that translation systems from different source language into the same target language have complementary strengths and weak- nesses in terms of translation performance and introduce an approach that ... See full document
10
Multi Source Neural Machine Translation with Missing Data
... However, this paradigm assumes that we have data in all of the languages that go into our multi- source system. For example, if we decide that En- glish and Spanish are our input languages and that we would like ... See full document
8
Encoding Source Language with Convolutional Neural Network for Machine Translation
... The Role of Guiding Signal It is slight sur- prising that the generic CNN can also achieve the gain on BLEU similar to that of BBN- JM, since intuitively generic CNN encodes the entire sentence and the representations ... See full document
11
Exploiting Source side Monolingual Data in Neural Machine Translation
... just source-side monolingual corpora rather than the synthetic par- allel ...age source-side monolingual data in NMT using a simple autoencoder and skip-thought ...sharing neural network framework to ... See full document
11
Dynamic Sentence Sampling for Efficient Training of Neural Machine Translation
... Josep Maria Crego, Jungi Kim, Guillaume Klein, Anabel Rebollo, Kathy Yang, Jean Senellart, Egor Akhanov, Patrice Brunelle, Aurelien Coquard, Yongchao Deng, Satoshi Enoue, Chiyo Geiss, Joshua Johanson, Ardas Khalsa, Raoum ... See full document
7
Target Foresight Based Attention for Neural Machine Translation
... based neural network for image caption task and ad- vance the state-of-the-art results; Yin et ...of machine translation, the idea of attention based neu- ral networks has been pioneered by Bahdanau ... See full document
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