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An In-depth Walkthrough on Evolution of Neural Machine Translation

2020-04-10 04:21:05
Rohan Jagtap, Dr. Sudhir N. Dhage

Abstract

Neural Machine Translation (NMT) methodologies have burgeoned from using simple feed-forward architectures to the state of the art; viz. BERT model. The use cases of NMT models have been broadened from just language translations to conversational agents (chatbots), abstractive text summarization, image captioning, etc. which have proved to be a gem in their respective applications. This paper aims to study the major trends in Neural Machine Translation, the state of the art models in the domain and a high level comparison between them.

Abstract (translated)

URL

https://arxiv.org/abs/2004.04902

PDF

https://arxiv.org/pdf/2004.04902.pdf


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