@InProceedings{dalvi-EtAl:2018:N18-2,
  author    = {Dalvi, Fahim  and  Durrani, Nadir  and  Sajjad, Hassan  and  Vogel, Stephan},
  title     = {Incremental Decoding and Training Methods for Simultaneous Translation in Neural Machine Translation},
  booktitle = {Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {493--499},
  abstract  = {We address the problem of simultaneous translation by modifying the Neural MT decoder to operate with dynamically built encoder and attention. We propose a tunable agent which decides the best segmentation strategy for a user-defined BLEU loss and Average Proportion (AP) constraint. Our agent outperforms previously proposed Wait-if-diff and Wait-if-worse agents (Cho and Esipova, 2016) on BLEU with a lower latency. Secondly we proposed data-driven changes to Neural MT training to better match the incremental decoding framework.},
  url       = {http://www.aclweb.org/anthology/N18-2079}
}