Thus, this research proposes a novel NMT-SMT hybrid framework that optimizes the baseline NMT comprising encoder–decoder with attention, by incrementally training it with the best translations of the ...

Abstract: Neural machine translation (NMT) models have achieved comparable results to ... enhances the model's robustness to domain shift by episodically exposing the encoder/decoder to an ...

We read the entire source sentence, understand its meaning, and then produce a translation. Neural Machine Translation (NMT) mimics that! Figure 1. Encoder-decoder architecture – example of a general ...

The NMT also uses bidirectional recurrent neural network also called as an encoder to process a source sentence into a vector for a second recurrent neural network called a decoder. This process is ...

We propose a new algorithm named BERT-fused model, in which we first use BERT to extract representations for an input sequence, and then the representations are fused with each layer of the encoder ...