Word Prediction for Amharic Online Handwriting Recognition

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Date

2008-07

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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. Keywords: Amharic Online Handwriting Recognition, Amharic word prediction model, N-gram model for Amharic word prediction, word prediction corpus

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Keywords

Amharic Online Handwriting Recognition; Amharic Word Prediction Model; N-Gram Model for Amharic Word Prediction; Word Prediction Corpus

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