A Survey of Next Words Prediction Models

Word prediction, also called language modeling, is one field of natural language processing that can help predict the next word. Next-word prediction technology has emerged as a crucial tool for enhancing text input efficiency and reducing spelling errors. Globally, people are spending a cumulative amount of time on their mobile devices, laptops, desktops, etc. for messaging, sending emails, banking, interacting through social media, and all other activities. It’s necessary to cut down on the time spent typing through these devices. This paper aims to provide a comprehensive overview of prior research in the field of word prediction, specifically focusing on the utilization of deep learning (DL), statistical approaches, and hybrid methodologies. The primary objective is to compare the outcomes achieved through these various techniques. This study concludes that the word prediction system can be categorized into four models, which are statistical, DL, pre-trained, and hybrid models, and concludes that the selection of an appropriate model for word prediction depends on several factors, such as the nature of the application, the availability of data, computational resources, and accuracy requirements.