@InProceedings{scarton-EtAl:2017:I17-3,
  author    = {Scarton, Carolina  and  Palmero Aprosio, Alessio  and  Tonelli, Sara  and  Mart\'{i}n Wanton, Tamara  and  Specia, Lucia},
  title     = {MUSST: A Multilingual Syntactic Simplification Tool},
  booktitle = {Proceedings of the IJCNLP 2017, System Demonstrations},
  month     = {November},
  year      = {2017},
  address   = {Tapei, Taiwan},
  publisher = {Association for Computational Linguistics},
  pages     = {25--28},
  abstract  = {We describe MUSST, a multilingual syntactic simplification tool. The tool sup-
	ports sentence simplifications for English, Italian and Spanish, and can be
	easily extended to other languages. Our implementation includes a set of
	general-purpose simplification rules, as well as a sentence selection module
	(to select sentences to be simplified) and a confidence model (to select only
	promising simplifications). The tool was implemented in the context of
	the European project SIMPATICO on text simplification for Public Administration
	(PA) texts. Our evaluation on sentences in the PA domain shows that we obtain
	correct simplifications for 76% of the simplified cases in English, 71% of the
	cases in Spanish. For Italian, the results are lower (38%) but the tool is
	still under development.},
  url       = {http://www.aclweb.org/anthology/I17-3007}
}