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Learning Phrase Representations Using RNN Encoder-Decoder For Statistical Machine Translation in Pytorch by Debasish Pradhan is a document available to read on EtoBox.

What is Learning Phrase Representations Using RNN Encoder-Decoder For Statistical Machine Translation in Pytorch about?

The paper presents a novel RNN Encoder–Decoder architecture aimed at enhancing phrase-based Statistical Machine Translation (SMT) by learning fixed-length vector representations of variable-length phrases. It introduces a gated hidden unit to improve memory control and manage long-range dependencies, achieving higher BLEU scores and better generalization in translation quality. This work marks a significant shift towards neural approaches in SMT and has influenced subsequent developments in sequence-to-sequ

Author

Debasish Pradhan

Language

EN