计算机科学
自然语言处理
语言模型
分层数据库模型
人工智能
语言学
词(群论)
缓存语言模型
通用网络语言
心理学
理解法
自然语言
哲学
数据挖掘
作者
Marc Brysbaert,Wouter Duyck
标识
DOI:10.1017/s1366728909990344
摘要
The Revised Hierarchical Model (RHM) of bilingual language processing dominates current thinking on bilingual language processing. Recently, basic tenets of the model have been called into question. First, there is little evidence for separate lexicons. Second, there is little evidence for language selective access. Third, the inclusion of excitatory connections between translation equivalents at the lexical level is likely to impede word recognition. Fourth, the connections between L2 words and their meanings are stronger than proposed in RHM. And finally, there is good evidence to make a distinction between language-dependent and language-independent semantic features. It is argued that the Revised Hierarchical Model cannot easily be adapted to incorporate these challenges and that a more fruitful way forward is to start from existing computational models of monolingual language processing and see how they can be adapted for bilingual input and output, as has been done in the Bilingual Interactive Activation model.
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