A Comprehensive Analysis of Deep Learning's Impact on Natural Language Processing

Abstract

The application of deep learning (DL) models has become significantly more widespread in recent years, which has facilitated significant development in the field of natural language processing (NLP). Through the enhancement of verbal interactions between humans and computers, NLP makes intelligent robots possible. The need for data-driven automation of semantic analysis has increased in response to recent advancements in processing capability as well as the appearance of enormous quantities of linguistic data. The enormous advancements made by deep learning techniques in the fields of computer vision, automatic speech recognition, and NLP have contributed to the widespread acceptance of data-driven initiatives. In this paper, NLP applications that can benefit from deep learning are classified. It highlights fundamental NLP tasks and applications, in addition to the ways in which deep learning might improve those jobs and applications. In our analysis, we compare various tactics to various modern models.