Neuro-Cognitive Computational Model of Automatic Lexical Acquisition

Kinam Park, WonHee Yu, Heuiseok Lim, Soonyoung Jung
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Abstract

This study is intended to design and implement an automatic lexical acquisition model based on cognitive neuroscience referring to the theory that mental lexicon structure is represented with full-listing and morphemic and that lexical forms accessed to mental lexicon upon word cognition takes a hybrid type. As the result of the study, we could simulate the lexical acquisition process of linguistic input through experiments and studying, and suggest a theoretical foundation for the order of acquitting certain grammatical categories. Also, the model of this study has shown proofs with which we can infer the type of the mental lexicon of the human cerebrum through full-list dictionary and decomposition dictionary which were automatically produced in the study.
自动词汇习得的神经认知计算模型
本研究旨在借鉴心理词汇结构以全表和语素表示、词汇认知时获取的词汇形式为混合型的理论,设计并实现基于认知神经科学的词汇自动习得模型。通过实验和研究,我们可以模拟语言输入的词汇习得过程,为某些语法范畴的习得顺序提供理论依据。同时,本研究的模型也为我们通过研究中自动生成的全表词典和分解词典来推断人脑心理词汇的类型提供了证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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