@InProceedings{zhou-EtAl:2016:COLING1,
  author    = {Zhou, Nina  and  Aw, AiTi  and  Lertcheva, Nattadaporn  and  Wang, Xuancong},
  title     = {A Word Labeling Approach to Thai Sentence Boundary Detection and POS Tagging},
  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     = {319--327},
  abstract  = {Previous studies on Thai Sentence Boundary Detection (SBD) mostly assumed
	sentence ends at a space disambiguation problem, which classified space either
	as an indicator for Sentence Boundary (SB) or non-Sentence Boundary (nSB). In
	this paper, we propose a word labeling approach which treats space as a normal
	word, and detects SB between any two words. This removes the restriction for SB
	to be oc-curred only at space and makes our system more robust for modern Thai
	writing. It is because in modern Thai writing, space is not consistently used
	to indicate SB. As syntactic information contributes to better SBD, we further
	propose a joint Part-Of-Speech (POS) tagging and SBD framework based on
	Factorial Conditional Random Field (FCRF) model. We compare the performance of
	our proposed ap-proach with reported methods on ORCHID corpus. We also
	performed experiments of FCRF model on the TaLAPi corpus. The results show that
	the word labelling approach has better performance than pre-vious space-based
	classification approaches and FCRF joint model outperforms LCRF model in terms
	of SBD in all experiments.},
  url       = {http://aclweb.org/anthology/C16-1031}
}