Machine Learning Powered Text Auto-Completion and Generation

A branch of artificial intelligence called “natural language processing” (NLP) helps computers comprehend human language. It combines the strength of linguistics and computer science to think about language rule, grammar and create intelligent systems capable of understanding, dissecting, and isolating meaning from text and speech. Using this concept, the research proposes a system which helps in minimizing the human effort by providing the features like text auto-completion and generation. Auto-completion is the process of completing a word, or a phrase, as people type in a document. The prediction is based on the most likely word among a set of frequently used terms. The text prediction task involves editing text with the fewest number of keystrokes possible. This method will suggest words that the user intended to write, and the system predicts next word related to the previous work. Text generation is a feature which is an enhanced version of Gmail's Smart Reply. This feature helps in generating a template of the mail by classifying the subject line. The goal of the proposed intelligent system is to assist human by increasing their typing speed and decreasing the number of keystrokes required to complete a word or a sentence. The suggested method is also very useful for multi-domain professionals who compose content, particularly those who frequently employ extensive, difficult-to-spell language that may be technical or non-technical.