An In-depth Walkthrough on Evolution of Neural Machine Translation

• URL: http://arxiv.org/abs/2004.04902v1
• Date: Fri, 10 Apr 2020 04:21:05 GMT
• Title: An In-depth Walkthrough on Evolution of Neural Machine Translation
• Authors: Rohan Jagtap, Dr. Sudhir N. Dhage
• Abstract summary: 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.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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