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Comprehension of Simple Quantifiers: Empirical Evaluation of a Computational Model
Author(s) -
Szymanik Jakub,
Zajenkowski Marcin
Publication year - 2010
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1111/j.1551-6709.2009.01078.x
Subject(s) - computer science , computational model , comprehension , simple (philosophy) , computational complexity theory , perspective (graphical) , cognition , computational linguistics , artificial intelligence , theoretical computer science , cognitive science , empirical research , automaton , cognitive psychology , natural language processing , psychology , mathematics , algorithm , programming language , epistemology , philosophy , statistics , neuroscience
We examine the verification of simple quantifiers in natural language from a computational model perspective. We refer to previous neuropsychological investigations of the same problem and suggest extending their experimental setting. Moreover, we give some direct empirical evidence linking computational complexity predictions with cognitive reality. In the empirical study we compare time needed for understanding different types of quantifiers. We show that the computational distinction between quantifiers recognized by finite‐automata and push‐down automata is psychologically relevant. Our research improves upon, the hypotheses and explanatory power of recent neuroimaging studies as well as provides evidence for the claim that human linguistic abilities are constrained by computational complexity.