@InProceedings{bentz-EtAl:2016:CL4LC,
  author    = {Bentz, Christian  and  Ruzsics, Tatyana  and  Koplenig, Alexander  and  Samardzic, Tanja},
  title     = {A Comparison Between Morphological Complexity Measures: Typological Data vs. Language Corpora},
  booktitle = {Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {142--153},
  abstract  = {Language complexity is an intriguing phenomenon argued to play an important
	role in both language learning and processing. The need to compare languages
	with regard to their complexity resulted in a multitude of approaches and
	methods, ranging from accounts targeting specific structural features to global
	quantification of variation more generally. In this paper, we investigate the
	degree to which morphological complexity measures are mutually correlated in a
	sample of more than 500 languages of 101 language families. We use human expert
	judgements from the World Atlas of Language Structures (WALS), and compare them
	to four quantitative measures automatically calculated from language corpora.
	These consist of three previously defined corpus-derived measures, which are
	all monolingual, and one new measure based on automatic word-alignment across
	pairs of languages. We find strong correlations between all the measures,
	illustrating that both expert judgements and automated approaches converge to
	similar complexity ratings, and can be used interchangeably.},
  url       = {http://aclweb.org/anthology/W16-4117}
}