Urdu T9 and Word prediction messaging System for Android

Word prediction in mobiles was not yet introduced before, this thesis addresses about it. It is more efficient then all previous techniques that are being used in mobiles. This technique predicts words on the basis of current words and is merged with word completion technique. It is made possible by using bi-gram model. Due to word perdition without typing a single letter a complete word can be typed and also user can choose a word of his/her requirement from prediction list. A frequently used word typed by user will always be on top of list. It improves the frequencies of all words typed by the user. A new word which is not present in dictionary can be added by the user and it appears in predations list after typing it for maximum three times. Software is tested by 3,000 characters and its results are 70 %, which are better than previous techniques like multi-tapping, word completion and without multi-tapping. Its significant point is that user can type faster.

Autorentext

Sana Shahzadi and Beenish Fatima: We have completed our Master of Information Technology from PUCIT University of the Punjab, Lahore Pakistan.Muhammad Kamran Malik: I am working at PUCIT, University of the Punjab, Lahore Pakistan as Assistant Professor. My area of Interest is Natural Language Processing.