AN ACTIVATION VERIFICATION MODEL FOR LETTER AND WORD RECOGNITION - THE WORD-SUPERIORITY EFFECT
AN ACTIVATION VERIFICATION MODEL FOR LETTER AND WORD RECOGNITION - THE WORD-SUPERIORITY EFFECT
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DOI：
10.1037/0033-295x.89.5.573
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发表时间：
1982-01-01
影响因子：
5.4
通讯作者：
SCHVANEVELDT, RW
中科院分区：
文献类型：
--
作者：
PAAP, KR;NEWSOME, SL;SCHVANEVELDT, RW
开发了字母和单词识别的激活验证模型，该模型可以预测864个单独刺激的2种强制选择性能，这些刺激要么是单词，拼写规则的非单词，要么是拼写不规则的非单词。该模型解释了为什么嵌入在单词中的字母比嵌入在非单词中的字母识别得更准确。编码算法使用经验确定的混淆矩阵来激活字母库和词典中的单元。当决策基于词汇信息时，预测性能会得到增强，因为词汇中的活动往往比字母表中的活动更能约束测试字母的身份。因此，该模型预测了单词相对于不规则非单词的较大优势，而单词相对于规则非单词的较小优势。预测的差异表明，仅在词汇约束的基础上就可以预测操纵词法和正字法的影响。在每个类（单词、规则非单词、不规则非单词）中，对单个项目的模拟反应和获得的反应之间存在显著的相关性。该模型与JL McClelland等人的交互激活模型（见1981-31825-001）进行了对比。（29 ref）（PsycINFO Database Record (c) 2016 APA，版权所有）
Developed an activation–verification model for letter and word recognition that yields predictions of 2-alternative forced-choice performance for 864 individual stimuli that are either words, orthographically regular nonwords, or orthographically irregular nonwords. The model explains why letters embedded in words are recognized more accurately than letters embedded in nonwords. The encoding algorithm uses empirically determined confusion matrices to activate units in both an alphabetum and a lexicon. Predicted performance is enhanced when decisions are based on lexical information, because activity in the lexicon tends to constrain the identity of test letters more than the activity in the alphabetum. Thus, the model predicts large advantages of words over irregular nonwords, and smaller advantages of words over regular nonwords. The predicted differences demonstrate that the effects of manipulating lexicality and orthography can be predicted on the basis of lexical constraint alone. Within each class (word, regular nonword, irregular nonword) there are significant correlations between the simulated and obtained responses on individual items. This model is contrasted with the interactive activation model of JL McClelland et al (see record 1981-31825-001).(29 ref)(PsycINFO Database Record (c) 2016 APA, all rights reserved)