14.5k citations · 22.4k across the 46 of their papers we have counts for
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End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results
Jan Chorowski, Dzmitry Bahdanau, Kyunghyun Cho +1
We replace the Hidden Markov Model (HMM) which is traditionally used in in continuous speech recognition with a bi-directional recurrent neural network encoder coupled to a recurre…
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau +1
Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks. The neural machine translation models often consist of a…
Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation
Jean Pouget-Abadie, Dzmitry Bahdanau, Bart van Merrienboer +2
The authors of (Cho et al., 2014a) have shown that the recently introduced neural network translation systems suffer from a significant drop in translation quality when translating…
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio
Neural machine translation is a recently proposed approach to machine translation. Unlike the traditional statistical machine translation, the neural machine translation aims at bu…
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre +4
In this paper, we propose a novel neural network model called RNN Encoder-Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of symbols into a…