Probability and surprisal in auditory comprehension of morphologically complex words

被引:61
作者
Balling, Laura Winther [3 ,4 ]
Baayen, R. Harald [1 ,2 ]
机构
[1] Univ Tubingen, Seminar Sprachwissensch, Tubingen, Germany
[2] Univ Alberta, Dept Linguist, Edmonton, AB, Canada
[3] Univ Aarhus, Dept Aesthet & Commun, DK-8000 Aarhus C, Denmark
[4] Copenhagen Business Sch, Dept Int Business Commun, Copenhagen, Denmark
关键词
Spoken word recognition; Shortlist B; Morphological processing; Uniqueness points; Neighborhood measures (cumulative) Surprisal; Kullback-Leibler divergence; Morphological family size; LEXICAL ACCESS; FAMILY-SIZE; RECOGNITION; DUTCH; FREQUENCY; MODEL; LANGUAGE; TRANSPARENCY; SEGMENTATION; SHORTLIST;
D O I
10.1016/j.cognition.2012.06.003
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Two auditory lexical decision experiments document for morphologically complex words two points at which the probability of a target word given the evidence shifts dramatically. The first point is reached when morphologically unrelated competitors are no longer compatible with the evidence. Adapting terminology from Marslen-Wilson (1984), we refer to this as the word's initial uniqueness point (UP1). The second point is the complex uniqueness point (CUP) introduced by Balling and Baayen (2008), at which morphologically related competitors become incompatible with the input. Later initial as well as complex uniqueness points predict longer response latencies. We argue that the effects of these uniqueness points arise due to the large surprisal (Levy, 2008) carried by the phonemes at these uniqueness points, and provide independent evidence that how cumulative surprisal builds up in the course of the word co-determines response latencies. The presence of effects of surprisal, both at the initial uniqueness point of complex words, and cumulatively throughout the word, challenges the Shortlist B model of Norris and McQueen (2008), and suggests that a Bayesian approach to auditory comprehension requires complementation from information theory in order to do justice to the cognitive cost of updating probability distributions over lexical candidates. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:80 / 106
页数:27
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