@InProceedings{ye-zhang-cai:2016:COLING,
  author    = {Ye, Na  and  Zhang, Guiping  and  Cai, Dongfeng},
  title     = {Interactive-Predictive Machine Translation based on Syntactic Constraints of Prefix},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {1797--1806},
  abstract  = {Interactive-predictive machine translation (IPMT) is a translation mode which
	combines machine translation technology and human behaviours. In the IPMT
	system, the utilization of the prefix greatly affects the interaction
	efficiency. However, state-of-the-art methods filter translation hypotheses
	mainly according to their matching results with the prefix on character level,
	and the advantage of the prefix is not fully developed. Focusing on this
	problem, this paper mines the deep constraints of prefix on syntactic level to
	improve the performance of IPMT systems. Two syntactic subtree matching rules
	based on phrase structure grammar are proposed to filter the translation
	hypotheses more strictly. Experimental results on LDC Chinese-English corpora
	show that the proposed method outperforms state-of-the-art phrase-based IPMT
	system while keeping comparable decoding speed.},
  url       = {http://aclweb.org/anthology/C16-1169}
}