Peran AI Dalam Menganalisis Produksi Bahasa: Studi Psikolinguistik Digital
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Abstract
From a psycholinguistic perspective, the goal of this study is to investigate how artificial intelligence (AI) can be used to understand and mimic human language creation. It investigates how artificial intelligence (AI), particularly ChatGPT and other natural language processing software, imitates human cognitive processes to generate language. Using a descriptive qualitative approach, this study investigates the similarities and differences between human and AI-based language production, focusing on Levelt's (1989) conceptualization, formulation, and articulation stages. The information was gathered through document analysis, a review of the literature, and observation of AI-generated language. The findings show that AI systems are getting better at simulating the linguistic structures, syntactic planning, and lexical access present in human speech. However, the lack of pragmatic, emotional, and cultural knowledge limits AI's ability to mimic real human conversation. The study's conclusions indicate that artificial intelligence (AI) is a crucial analytical paradigm in digital psycholinguistics that creates new opportunities for language research and creative teaching.
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References
Bender, E. M., & Koller, A. (2020). Climbing towards NLU: On meaning, form, and understanding. Proceedings of the 58th Annual Meeting of the ACL, 5185–5198.
Carroll, D. W. (2008). Psychology of language. Thomson Wadsworth.
Chomsky, N. (2006). Language and mind. Cambridge University Press.
Clark, A. (2016). Surfing uncertainty: Prediction, action, and the embodied mind. Oxford University Press.
Cutting, J. C. (2011). Psychology of language and communication. Psychology Press.
Ellis, N. C. (2016). Cognitive approaches to second language acquisition. Cambridge University Press.
Field, J. (2003). Psycholinguistics: A resource book for students. Routledge.
Fodor, J. (1975). The language of thought. Harvard University Press.
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
Grice, H. P. (1975). Logic and conversation. Harvard University Press.
Harley, T. (2014). The psychology of language: From data to theory. Psychology Press.
Hartmann, E. (2021). AI and cognition: Understanding computational models of mind. Springer.
Jurafsky, D., & Martin, J. H. (2023). Speech and language processing (3rd ed.). Pearson.
Levelt, W. J. M. (1989). Speaking: From intention to articulation. MIT Press.
Marr, D. (1982). Vision: A computational investigation into the human representation and processing of visual information. MIT Press.
Mitchell, T. M. (1997). Machine learning. McGraw-Hill.
OpenAI. (2024). ChatGPT technical report. OpenAI Publications.
Pinker, S. (1994). The language instinct. William Morrow.
Rumelhart, D. E., & McClelland, J. L. (1986). Parallel distributed processing: Explorations in the microstructure of cognition (Vol. 1). MIT Press.
Snowling, M. J., & Hulme, C. (2012). The science of reading: A handbook. Wiley-Blackwell.
Spivey, M. J., McRae, K., & Joanisse, M. F. (2012). The Cambridge handbook of psycholinguistics. Cambridge University Press.
Tomasello, M. (2003). Constructing a language: A usage-based theory of language acquisition. Harvard University Press
Traxler, M. J. (2012). Introduction to psycholinguistics: Understanding language science. Blackwell.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30.
Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9(4), 625–636.