@InProceedings{banerjee-bhattacharyya:2018:W18-12,
  author    = {Banerjee, Tamali  and  Bhattacharyya, Pushpak},
  title     = {Meaningless yet meaningful: Morphology grounded subword-level NMT},
  booktitle = {Proceedings of the Second Workshop on Subword/Character LEvel Models},
  month     = {June},
  year      = {2018},
  address   = {New Orleans},
  publisher = {Association for Computational Linguistics},
  pages     = {55--60},
  abstract  = {We explore the use of two independent subsystems Byte Pair Encoding (BPE) and Morfessor as basic units for subword-level neural machine translation (NMT). We show that, for linguistically distant language-pairs Morfessor-based segmentation algorithm produces significantly better quality translation than BPE. However, for close language-pairs BPE-based subword-NMT may translate better than Morfessor-based subword-NMT. We propose a combined approach of these two segmentation algorithms Morfessor-BPE (M-BPE) which outperforms these two baseline systems in terms of BLEU score. Our results are supported by experiments on three language-pairs: English-Hindi, Bengali-Hindi and English-Bengali.},
  url       = {http://www.aclweb.org/anthology/W18-1207}
}