Magnuson James S, Tanenhaus Michael K, Aslin Richard N, Dahan Delphine
Department of Psychology, Columbia University, New York, New York 10027, USA.
J Exp Psychol Gen. 2003 Jun;132(2):202-27. doi: 10.1037/0096-3445.132.2.202.
The time course of spoken word recognition depends largely on the frequencies of a word and its competitors, or neighbors (similar-sounding words). However, variability in natural lexicons makes systematic analysis of frequency and neighbor similarity difficult. Artificial lexicons were used to achieve precise control over word frequency and phonological similarity. Eye tracking provided time course measures of lexical activation and competition (during spoken instructions to perform visually guided tasks) both during and after word learning, as a function of word frequency, neighbor type, and neighbor frequency. Apparent shifts from holistic to incremental competitor effects were observed in adults and neural network simulations, suggesting such shifts reflect general properties of learning rather than changes in the nature of lexical representations.
口语单词识别的时间进程在很大程度上取决于一个单词及其竞争者（即邻居词，发音相似的单词）的频率。然而，自然词汇表中的变异性使得对频率和邻居词相似性进行系统分析变得困难。人工词汇表被用来实现对单词频率和语音相似性的精确控制。在单词学习期间和之后，通过眼动追踪提供了词汇激活和竞争的时间进程测量（在执行视觉引导任务的口语指令期间），作为单词频率、邻居词类型和邻居词频率的函数。在成年人和神经网络模拟中都观察到了从整体竞争者效应到增量竞争者效应的明显转变，这表明这种转变反映了学习的一般特性，而不是词汇表征性质的变化。
