Simulating Language-specific and Language-general Effects in a Statistical Learning Model of Chinese Reading.
Simulating Language-specific and Language-general Effects in a Statistical Learning Model of Chinese Reading.
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DOI：
10.1016/j.jml.2009.05.001
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发表时间：
2009-08-02
影响因子：
4.3
通讯作者：
Zevin, Jason D.
中科院分区：
文献类型：
--
作者：
Yang, Jianfeng;McCandliss, Bruce D.;Shu, Hua;Zevin, Jason D.
许多阅读理论模型都假设不同的写作系统需要不同的加工假设。例如，人们经常声称，汉语中的印-音映射不是以次词汇的方式表示或处理的。我们提出了一个连接主义模型，该模型使用与英语相同的功能结构和学习规则来学习汉字的印刷体到声音的映射。该模型预测了项目频率和印刷到声音一致性之间的交互作用，类似于在英语中发现的情况，以及汉语特有的语言规律性效应。使用与模型相同的测试项的行为命名实验证实了这些预测。语料库的属性和对训练过程中演变的内部表征的分析表明，该模型能够利用“语音成分”中的信息，“语音成分”是一种大小可变的子词汇结构，传达了有关发音的概率信息。结果表明，成人在不同书写系统中的阅读表现可以解释为，将相同的学习机制应用于书写系统的特定输入统计数据，这既受文化的影响，也受视觉媒介交流口语的迫切需要的影响。
Many theoretical models of reading assume that different writing systems require different processing assumptions. For example, it is often claimed that print-to-sound mappings in Chinese are not represented or processed sub-lexically. We present a connectionist model that learns the print to sound mappings of Chinese characters using the same functional architecture and learning rules that have been applied to English. The model predicts an interaction between item frequency and print-to-sound consistency analogous to what has been found for English, as well as a language-specific regularity effect particular to Chinese. Behavioral naming experiments using the same test items as the model confirmed these predictions. Corpus properties and the analyses of internal representations that evolved over training revealed that the model was able to capitalize on information in “phonetic components” – sub-lexical structures of variable size that convey probabilistic information about pronunciation. The results suggest that adult reading performance across very different writing systems may be explained as the result of applying the same learning mechanisms to the particular input statistics of writing systems shaped by both culture and the exigencies of communicating spoken language in a visual medium.
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影响因子：
3.7
作者：
Harm, MW;McCandliss, BD;Seidenberg, MS
通讯作者：
Seidenberg, MS
DOI：
10.3758/bf03195503
发表时间：
2003-02-01
期刊：
BEHAVIOR RESEARCH METHODS INSTRUMENTS & COMPUTERS
影响因子：
--
作者：
Forster, KI;Forster, JC
通讯作者：
Forster, JC
DOI：
10.1037/0278-7393.30.2.530
发表时间：
2004-03-01
影响因子：
2.6
作者：
Ding, GS;Peng, DL;Taft, M
通讯作者：
Taft, M
影响因子：
3.5
作者：
Chen, HC;Shu, H
通讯作者：
Shu, H
影响因子：
4.3
作者：
Feldman, LB;Siok, WWT
通讯作者：
Siok, WWT