Computational Linguistics: Text Prediction and Sentence Correction

Abstract

Language in this growing technology world text became the medium to communicate socially. Even though desktop computers have existed since a long time, the method of typing and feeding input has not changed much. Versions after versions of popular text editors have come, and yet no editor has addressed the difficulty of predicting the next
possible word and correction of predicted sentence. Also, predictive editors cease to exist in desktop computers even today. This paper aims to predict the next frequent word according to the trained corpus using the n-gram model and even checks the spelling of the entered word. In addition, it checks for the correction of sentence according to grammatical rules. This in proposed method it explores the use of a new software for the input on desktops, which relies on a dynamic predictive algorithm using n-grams and suffix trees to significantly reduce the effort of typing.