Neural Machine Translation

TL;DR

This chapter provides a comprehensive overview of neural machine translation, covering foundational neural network concepts, the dominant attentional sequence-to-sequence model, recent improvements, alternative architectures, and ongoing challenges.

Contribution

It serves as an educational resource summarizing the state-of-the-art in neural machine translation as of 2017.

Findings

Detailed explanation of the attentional sequence-to-sequence model

Discussion of recent refinements and alternative architectures

Identification of key challenges in neural machine translation

Abstract

Draft of textbook chapter on neural machine translation. a comprehensive treatment of the topic, ranging from introduction to neural networks, computation graphs, description of the currently dominant attentional sequence-to-sequence model, recent refinements, alternative architectures and challenges. Written as chapter for the textbook Statistical Machine Translation. Used in the JHU Fall 2017 class on machine translation.