Predicting sentence using N-gram language model for Nepali language

Abstract

Sentence completion is a real time ubiquitous feature directed to predict a succeeding words sequence, an appropriate completion of a given initial text fragment. Sentence completion able a user to retrieve desired information with little knowledge over exact keywords and with least typing efforts. Under statistical method, this work will deal with N-gram method to predict the remaining part of sentence for Nepali language using Viterbi as a decoding algorithm. By analyzing the result of this work, Trigram Prediction Model is more accurate than Bigram Prediction Model. To get the best result, this work recommends taking a large corpus with sufficient repetition of words.