title: Large-scale evidence of dependency length minimization in 37 languages.
abstract: Explaining the variation between human languages and the constraints on that variation is a core goal of linguistics. In the last 20 y, it has been claimed that many striking universals of cross-linguistic variation follow from a hypothetical principle that dependency length--the distance between syntactically related words in a sentence--is minimized. Various models of human sentence production and comprehension predict that long dependencies are difficult or inefficient to process; minimizing dependency length thus enables effective communication without incurring processing difficulty. However, despite widespread application of this idea in theoretical, empirical, and practical work, there is not yet large-scale evidence that dependency length is actually minimized in real utterances across many languages; previous work has focused either on a small number of languages or on limited kinds of data about each language. Here, using parsed corpora of 37 diverse languages, we show that overall dependency lengths for all languages are shorter than conservative random baselines. The results strongly suggest that dependency length minimization is a universal quantitative property of human languages and support explanations of linguistic variation in terms of general properties of human information processing.
authors.affiliation: Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 futrell@mit.edu.
authors.forename: Richard
authors.initials: R
authors.lastname: Futrell
authors.affiliation: Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139.
authors.forename: Kyle
authors.initials: K
authors.lastname: Mahowald
authors.affiliation: Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139.
authors.forename: Edward
authors.initials: E
authors.lastname: Gibson
mesh_terms: D032882:Comprehension / Q000502:physiology*; D006801:Humans; D007802:Language; D008037:Linguistics / Q000379:methods*; D008962:Models, Theoretical; D012044:Regression Analysis
keywords: language processing; language universals; quantitative linguistics