@InProceedings{katerenchuk:2017:EACLshort,
  author    = {Katerenchuk, Denys},
  title     = {Age Group Classification with Speech and Metadata Multimodality Fusion},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {188--193},
  abstract  = {Children comprise a significant proportion
	of TV viewers and it is worthwhile to customize
	the experience for them. However,
	identifying who is a child in the audience
	can be a challenging task. We present initial
	studies of a novel method which combines
	utterances with user metadata. In
	particular, we develop an ensemble of different
	machine learning techniques on different
	subsets of data to improve child detection.
	Our initial results show an 9.2%
	absolute improvement over the baseline,
	leading to a state-of-the-art performance.},
  url       = {http://www.aclweb.org/anthology/E17-2030}
}