BEHAVIORAL AND COMPUTATIONAL STUDIES OF MORPHOLOGY

形态学的行为和计算研究

• 批准号: 2891113
• 负责人: MARK S SEIDENBERG
• 金额: $ 12.97万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-09-10 至 2003-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2891113
• 关键词: behavioral /social science research tag; clinical research; communication behavior; computational neuroscience; computer simulation; human subject; language; memory; neural information processing; phonology; psychological models; reading; semantics; syntax

DESCRIPTION (Adapted from applicant's abstract): This proposal describes research on inflectional and derivational morphology and their role in reading and related tasks. Morphology is the aspect of language concerning the forms of words. The issues to be addressed concern how this information is represented in lexical memory; how it relates to other types of information including orthography, phonology, and semantics; and how it is used in processing. The research utilizes both behavioral studies of skilled language users and computer simulation modeling. The issues are framed in terms of connectionist principles concerning knowledge representation, acquisition, and processing that were developed in previous research on reading simple, monomorphemic words. The proposed research attempts to extend this theoretical framework to the processing of more complex words. The main emphasis of the research is on the quasiregular character of inflectional and derivational morphology: the fact that both systems are productive and can be described as "rule-governed" but also admit many exceptions that deviate from what is predicted from the rules. These phenomena have standardly been treated within dual-route models of lexical access in which there are separate mechanisms for the rule-governed cases and exceptions. Connectionist models provide an alternative approach in which all forms are governed by a single network. The experiments focus on phenomena that differentiate the dual- and single mechanism approaches in both inflectional and derivational domains. The theoretical account is also tested by implementing computational models with the goal of simulating behavioral data in close detail.

描述（根据申请人的摘要改编）：该提案描述 研究拐点和衍生形态及其在 阅读和相关任务。 形态学是语言有关的方面 单词的形式。 要解决的问题涉及此信息如何 在词汇记忆中表示；它如何与其他类型的 信息在内，包括拼字法，语音和语义；以及如何 用于处理。 该研究利用了两项行为研究 熟练的语言用户和计算机模拟建模。 问题是 根据知识的连接主义原则构建 以前开发的表示，获取和处理 关于阅读简单的单态单词的研究。 拟议的研究 试图将这个理论框架扩展到更多的处理 复杂的词。 该研究的主要重点在于Quasiregular 拐点和衍生形态的特征：两者都 系统是富有成效的，可以描述为“规则管理”，但也可以描述 承认许多偏离规则预测的例外。 这些现象已在双路线模型中得到了标准处理 词汇访问，其中有单独的规则机制 案例和例外。 连接主义者模型提供了另一种方法 其中所有形式均由一个网络支配。 实验重点 关于区分双重和单一机制接近的现象 拐点和派生域。 理论上也是 通过实施计算模型进行测试以模拟 行为数据密切详细。