Neural Hidden Markov Model for Machine Translation

Abstract

This work aims to investigate alternative neural machine translation (NMT) approaches and thus proposes a neural hidden Markov model (HMM) consisting of neural network-based alignment and lexicon models. The neural models make use of encoder and decoder components, but drop the attention component.