Hybrid Neural Network Alignment and Lexicon Model in Direct HMM for Statistical Machine Translation
Weiyue Wang, Tamer Alkhouli, Derui Zhu, Hermann Ney · 2017
Recently, the neural machine translation systems showed their promising performance and surpassed the phrase-based systems for most translation tasks.Retreating into conventional concepts machine translation while utilizing effective neural models is vital for comprehending the leap accomplished by neural machine translation over phrase-based methods.This work proposes a direct hidden Markov model (HMM) with neural network-based lexicon and alignment models, which are trained jointly using the Baum-Welch algorithm.The direct HMM is applied to rerank the n-best list created by a state-of-the-art phrase-based translation system and it provides improvements by up to 1.0% BLEU scores on two different translation tasks.