@InProceedings{huang-EtAl:2017:SIGHAN-9,
  author    = {Huang, Guoping  and  Zhang, Jiajun  and  Zhou, Yu  and  Zong, Chengqing},
  title     = {Learning from Parenthetical Sentences for Term Translation in Machine Translation},
  booktitle = {Proceedings of the 9th SIGHAN Workshop on Chinese Language Processing},
  month     = {December},
  year      = {2017},
  address   = {Taiwan},
  publisher = {Association for Computational Linguistics},
  pages     = {37--45},
  abstract  = {Terms extensively exist in specific domains, and term translation plays a
	critical role in domain-specific machine translation (MT) tasks. However, it's
	a challenging task to translate them correctly for the huge number of
	pre-existing terms and the endless new terms. To achieve better term
	translation quality, it is necessary to inject external term knowledge into the
	underlying MT system. Fortunately, there are plenty of term translation
	knowledge in parenthetical sentences on the Internet. In this paper, we propose
	a simple, straightforward and effective framework to improve term translation
	by learning from parenthetical sentences. This framework includes: (1) a
	focused web crawler; (2) a parenthetical sentence filter, acquiring
	parenthetical sentences including bilingual term pairs; (3) a term translation
	knowledge extractor, extracting bilingual term translation candidates; (4) a
	probability learner, generating the term translation table for MT decoders. The
	extensive experiments demonstrate that our proposed framework significantly
	improves the translation quality of terms and sentences.},
  url       = {http://www.aclweb.org/anthology/W17-6005}
}