Add to ORKGIn this paper, we propose a novel neu-ral network model called RNN Encoder– Decoder that consists of two recurrent neural networks (RNN). One RNN en-codes a sequence of symbols into a fixed-length vector representation, and the other decodes the representation into another se-quence of symbols. The encoder and de-coder of the proposed model are jointly trained to maximize the conditional prob-ability of a target sequence given a source sequence. The performance of a statisti-cal machine translation system is empiri-cally found to improve by using the con-ditional probabilities of phrase pairs com-puted by the RNN Encoder–Decoder as an additional feature in the existing log-linear model. Qualitatively, we show that the proposed model learns ...
With economic globalization and the rapid development of the Internet, the connections between diffe...
The goal of this thesis is to describe and build a system for neural machine translation. System is ...
Most statistical machine translation (SMT) systems are modeled using a log-linear framework. Althoug...
In this paper, we propose a novel neu-ral network model called RNN Encoder– Decoder that consists of...
In this paper, we propose a novel recursive recurrent neural network (R2NN) to mod-el the end-to-end...
Neural machine translation is a relatively new approach to statistical machine trans-lation based pu...
This work presents two different trans-lation models using recurrent neural net-works. The first one...
This work presents two different trans-lation models using recurrent neural net-works. The first one...
The inability to model long-distance depen-dency has been handicapping SMT for years. Specifically, ...
In this era of globalization, it is quite likely to come across people or community who do not share...
We introduce recurrent neural network-based Minimum Translation Unit (MTU) models which make predict...
We introduce recurrent neural network-based Minimum Translation Unit (MTU) models which make predict...
This paper tackles the sparsity problem in estimating phrase translation probabilities by learning c...
Virtually any modern speech recognition system relies on count-based language models. In this thesis...
With economic globalization and the rapid development of the Internet, the connections between diffe...
With economic globalization and the rapid development of the Internet, the connections between diffe...
The goal of this thesis is to describe and build a system for neural machine translation. System is ...
Most statistical machine translation (SMT) systems are modeled using a log-linear framework. Althoug...
In this paper, we propose a novel neu-ral network model called RNN Encoder– Decoder that consists of...
In this paper, we propose a novel recursive recurrent neural network (R2NN) to mod-el the end-to-end...
Neural machine translation is a relatively new approach to statistical machine trans-lation based pu...
This work presents two different trans-lation models using recurrent neural net-works. The first one...
This work presents two different trans-lation models using recurrent neural net-works. The first one...
The inability to model long-distance depen-dency has been handicapping SMT for years. Specifically, ...
In this era of globalization, it is quite likely to come across people or community who do not share...
We introduce recurrent neural network-based Minimum Translation Unit (MTU) models which make predict...
We introduce recurrent neural network-based Minimum Translation Unit (MTU) models which make predict...
This paper tackles the sparsity problem in estimating phrase translation probabilities by learning c...
Virtually any modern speech recognition system relies on count-based language models. In this thesis...
With economic globalization and the rapid development of the Internet, the connections between diffe...
With economic globalization and the rapid development of the Internet, the connections between diffe...
The goal of this thesis is to describe and build a system for neural machine translation. System is ...
Most statistical machine translation (SMT) systems are modeled using a log-linear framework. Althoug...