SHERP

Dependency Distance as a Metric of Language Comprehension Difficulty

Cited 0 time in webofscience Cited 0 time in scopus
Authors
Liu, Haitao
Issue Date
2008
Publisher
Institute for Cognitive Science, Seoul National University
Citation
Journal of Cognitive Science, vol.9, no.2, pp. 159-191
Keywords
dependency distancecomprehension difficultytreebankcognitive cost
Abstract
Linguistic complexity is a measure of the cognitive difficulty of human
language processing. The present paper proposes dependency distance, in the
framework of dependency grammar, as an insightful metric of complexity.
Three hypotheses are formulated: (1) The human language parser prefers linear
orders that minimize the average dependency distance of the recognized
sentence (2) There is a threshold that the average dependency distance of most
sentences or texts of human languages does not exceed (3) Grammar and
cognition combine to keep dependency distance within the threshold. Twenty
corpora from different languages with dependency syntactic annotation are used
to test these hypotheses. The paper reports the average dependency distance in
these corpora and analyzes the factors which influence dependency distance.
The findings — that average dependency distance has a tendency to be
minimized in human language and that there is a threshold of less than 3 words
in average dependency distance and grammar plays an important role in
constraining distance —support all three hypotheses, although some questions
are still open for further research.
ISSN
1598-2327
Language
English
URI
http://hdl.handle.net/10371/70907
Files in This Item:
There are no files associated with this item.
Appears in Collections:
College of Humanities (인문대학)Institute for Cognitive Science (인지과학연구소)Journal of Cognitive Science (인지과학작업)Journal of Cognitive Science (인지과학작업) vol.09 (2008)
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse