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All Journal Journal of Advances in Linguistics and English Teaching (JALET)
Muhammad Hasyimsyah Batubara
Sekolah Tinggi Agama Islam Negeri Mandailing Natal
Humanities Education Languange, Linguistic, Communication & Media Social Sciences

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Mental Lexicon and Memory Access: How Vocabulary is Stored in the Mind Citra Tiurnida Panggabean; Muhammad Hasyimsyah Batubara
Journal of Advances in Linguistics and English Teaching (JALET) Vol. 1 No. 2 (2025): July-December 2025
Publisher : Perkumpulan Madani Publisher Indonesia

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Abstract

This research aims to examine the structure and access of the mental lexicon in human memory through the psycholinguistic approach. The current study utilizes the qualitative descriptive approach by conducting a systematic literature review. The result shows that the access of the lexical knowledge is not constant, considering the frequency of the word, the contextual cue, and the meaning relationship, because it affects the language comprehension and production. The result also shows that the mental lexicon is hierarchically organized for effective lexical retrieval when people use language. This article concludes that the knowledge of the structure and the access of the mental lexicon is very significant for language acquisition processes and for the analysis of language disorders, including aphasia and dyslexia.
Psycholinguistics and Artificial Intelligence: A Comparative Analysis of Human and Machine Language Processing Mechanisms Habib Azizi Nasution; Muhammad Hasyimsyah Batubara
Journal of Advances in Linguistics and English Teaching (JALET) Vol. 1 No. 2 (2025): July-December 2025
Publisher : Perkumpulan Madani Publisher Indonesia

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Abstract

The rapid development of Artificial Intelligence (AI), particularly Natural Language Processing (NLP), has brought together two fundamental disciplines: Psycholinguistics and Computer Science. This research seeks to bridge the theoretical gap between how the human brain processes and generates language (psycholinguistics) and how machines model and replicate these processes (AI). This research employed a comparative-analytical literature review. Data was collected from leading academic journals focused on AI language models (such as Transformer and Large Language Models/LLMs) and theories of human language processing (such as Serial Processing and Connectionist Models). The analysis focused on three main dimensions: lexicon acquisition, syntactic processing, and pragmatic understanding. It was found that while modern AI excels at predicting word order and syntactic structure based on probability (like statistical approaches in cognition), it still falls short of fully replicating semantic processing tied to experience, awareness, and social context (a hallmark of human processing). Current AI models demonstrate impressive speeds in lexical inference but often fail at tasks requiring a theory of mind or a multi-layered understanding of pragmatics. Integrating psycholinguistic principles into AI architectures holds great potential for developing systems that are not only efficient but also more natural and human-like in their interactions. Further research is needed to build AI models that reflect the complex bottom-up and top-down processes in the human brain.
Co-Authors Citra Tiurnida Panggabean Habib Azizi Nasution