Dell Gary S, Oppenheim Gary M, Kittredge Audrey K
University of Illinois, Urbana-Champaign.
Lang Cogn Process. 2008 Jun;23(4):583-608. doi: 10.1080/01690960801920735.
Retrieving a word in a sentence requires speakers to overcome syntagmatic, as well as paradigmatic interference. When accessing cat in "The cat chased the string," not only are similar competitors such as dog and cap activated, but also other words in the planned sentence, such as chase and string. We hypothesize that both types of interference impact the same stage of lexical access, and review connectionist models of production that use an error-driven learning algorithm to overcome that interference. This learning algorithm creates a mechanism that limits syntagmatic interference, the syntactic "traffic cop," a configuration of excitatory and inhibitory connections from syntactic-sequential states to lexical units. We relate the models to word and sentence production data, from both normal and aphasic speakers.
在句子中检索一个单词要求说话者克服组合关系以及聚合关系的干扰。当在“The cat chased the string”中提取“cat”时,不仅像“dog”和“cap”这样相似的竞争词会被激活,而且计划句子中的其他单词,如“chase”和“string”也会被激活。我们假设这两种干扰会影响词汇提取的同一阶段,并回顾使用错误驱动学习算法来克服这种干扰的生成联结主义模型。这种学习算法创建了一种机制来限制组合关系的干扰,即句法“交通警察”,它是从句法序列状态到词汇单元的兴奋性和抑制性连接的一种配置。我们将这些模型与正常和失语症患者的单词和句子生成数据联系起来。