@InProceedings{vanzo-EtAl:2017:RoboNLP,
  author    = {Vanzo, Andrea  and  Croce, Danilo  and  Basili, Roberto  and  Nardi, Daniele},
  title     = {Structured Learning for Context-aware Spoken Language Understanding of Robotic Commands},
  booktitle = {Proceedings of the First Workshop on Language Grounding for Robotics},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {25--34},
  abstract  = {Service robots are expected to operate in specific environments, where the
	presence of humans plays a key role. A major feature of such robotics platforms
	is thus the ability to react to spoken commands. This requires the
	understanding of the user utterance with an accuracy able to trigger the robot
	reaction.
	Such correct interpretation of linguistic exchanges depends on physical,
	cognitive and language-dependent aspects related to the environment. In this
	work, we present the empirical evaluation of an adaptive Spoken Language
	Understanding chain for robotic commands, that explicitly depends on the
	operational environment during both the learning and recognition stages. The
	effectiveness of such a context-sensitive command interpretation is tested
	against an extension of an already existing corpus of commands, that introduced
	explicit perceptual knowledge: this enabled deeper measures proving that more
	accurate disambiguation capabilities can be actually obtained.},
  url       = {http://www.aclweb.org/anthology/W17-2804}
}