Semantic transparency in free stems: The effect of Orthography-Semantics Consistency on word recognition

被引:48
作者
Marelli, Marco [1 ]
Amenta, Simona [2 ]
Crepaldi, Davide [2 ]
机构
[1] Univ Trento, Ctr Mind Brain Sci, I-38068 Rovereto, TN, Italy
[2] Univ Milano Bicocca, Dept Psychol, Milan, Italy
关键词
Megastudies; Visual word identification; Distributional semantic models; Orthography-Semantics Consistency; THEN-MEANING ACCOUNTS; LEXICAL ACCESS; MORPHOLOGICAL DECOMPOSITION; PREFIXED WORDS; FAMILY-SIZE; FREQUENCY; MODEL; FORM; SEGMENTATION; COOCCURRENCE;
D O I
10.1080/17470218.2014.959709
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
A largely overlooked side effect in most studies of morphological priming is a consistent main effect of semantic transparency across priming conditions. That is, participants are faster at recognizing stems from transparent sets (e.g., farm) in comparison to stems from opaque sets (e.g., fruit), regardless of the preceding primes. This suggests that semantic transparency may also be consistently associated with some property of the stem word. We propose that this property might be traced back to the consistency, throughout the lexicon, between the orthographic form of a word and its meaning, here named Orthography-Semantics Consistency (OSC), and that an imbalance in OSC scores might explain the "stem transparency" effect. We exploited distributional semantic models to quantitatively characterize OSC, and tested its effect on visual word identification relying on large-scale data taken from the British Lexicon Project (BLP). Results indicated that (a) the "stem transparency" effect is solid and reliable, insofar as it holds in BLP lexical decision times (Experiment 1); (b) an imbalance in terms of OSC can account for it (Experiment 2); and (c) more generally, OSC explains variance in a large item sample from the BLP, proving to be an effective predictor in visual word access (Experiment 3).
引用
收藏
页码:1571 / 1583
页数:13
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