• Corpus ID: 17078659

Guided Alignment Training for Topic-Aware Neural Machine Translation

@inproceedings{Chen2016GuidedAT,
  title={Guided Alignment Training for Topic-Aware Neural Machine Translation},
  author={Wenhu Chen and Evgeny Matusov and Shahram Khadivi and Jan-Thorsten Peter},
  booktitle={Conference of the Association for Machine Translation in the Americas},
  year={2016}
}
In this paper, we propose an effective way for biasing the attention mechanism of a sequence-to-sequence neural machine translation (NMT) model towards the well-studied statistical word alignment models. We show that our novel guided alignment training approach improves translation quality on real-life e-commerce texts consisting of product titles and descriptions, overcoming the problems posed by many unknown words and a large type/token ratio. We also show that meta-data associated with input… 

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