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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1336

Title: Word Prediction for Amharic Online Handwriting Recognition
Authors: Nesredien, Suleiman
Advisors: 1. Solomon Atnafu (Ph. D.)
Keywords: Amharic Online Handwriting Recognition
Amharic word prediction model
N-gram model for Amharic word prediction
word prediction corpus
Copyright: 2008
Date Added: 2-Sep-2008
Publisher: Addis Ababa University
Abstract: Online handwriting recognition, keypads, soft keys are some of the data entry techniques used to enter data into mobile devices, such as smart phone, PDA etc. Data entry in these devices could be either predictive or non-predictive. A word prediction method is a data entry technique in which the first few characters of the word is written and the remaining are predicted. Among the data entry techniques, online handwriting recognition is commonly used for handheld devices such as PDAs. When online handwriting recognition is combined with word prediction, the data entry process will be more efficient. In this work, we have proposed a word prediction model for Amharic online handwriting recognition. To design the model: a corpus of 131,399 Amharic words is prepared to extract statistical information that is used to determine the value of N for the N-gram model, where the value two (2) is considered as a result of the analyses made a combination of an Amharic dictionary (lexicon) and a list of names of persons and places with a total size of 17,137 has been used. To show the validity of the word prediction model and the algorithm designed, a prototype is developed. Experiment is also conducted to measure the accuracy of the word prediction engine and a prediction accuracy of 81.39% is achieved
Description: A Thesis Submitted to the School of Graduate Studies of Addis Ababa University in Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Science
URI: http://hdl.handle.net/123456789/1336
Appears in:Thesis - Computer Science

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