A Novel approach to Computational Linguistics

Comparison of the Processes of Machine Learning and Language Acquisition and Implications

Abstract

The intersection between linguistics and machine learning is a field that has only recently gained popularity. However, due to its stark disparity of quantitative and qualitative methods, not much insight has been obtained through the intersection of the 2 fields of study. This study, aims to address that problem through a comparative approach of the process of first language acquisition, having its implications in the field of psycholinguistics, with the aim for 21st century parents to follow effective practices for their children to achieve fluency of their respective first language. The results demonstrated 5 thematic comparisons of the implications of machine learning in language acquisition. Through the findings of the study, machine learning and its process helps one bolster one’s understanding of how to systematically and effectively “train” or teach a child their first language with the goal of achieving fluency, maximizing the accuracy, rate, and prosody of language.