Review of the Development of Input Word Prediction

Abstract

As one of the important applications in the field of human-computer interaction, input word prediction has made great progress in recent years.This paper reviews and summarizes the development process of input word prediction technology, from the early statistical model-based method to the current deep learning-based technology application, describes its development trajectory and the representative algorithms of each technology.In addition, this paper also analyzes the current problems and challenges faced by input method word prediction, such as language model modeling, user personalized needs, multi-language input and other aspects of the problem, and discusses the future development trend, including the combination of multi-modal information, fusion reinforcement learning and other new technologies.Finally, this paper also looks forward to the extensive application prospects of input word prediction technology in many fields, and its potential contribution to improving user input efficiency, improving user experience and promoting the development of natural language technology.